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MON 9 DEC
noon
Registration (East & West)
(ends 6:00 PM)

TUE 10 DEC
6:30 a.m.
Expo Talk Panel:
Transforming Asset Management Research with Generative AI: From Data Curation to Idea Generation and Implementation
(ends 7:30 AM)
Expo Talk Panel:
AI for Autonomous Driving at Scale
(ends 7:30 AM)
Expo Talk Panel:
AI Verification & Validation: Trends, Applications, and Challenges
(ends 7:30 AM)
Expo Talk Panel:
Onboarding Generative AI at the Edge: Challenges and Solutions from Industrial Research
(ends 7:30 AM)
Expo Talk Panel:
Incentivizing Collaborative AI: A Decentralized Approach to Scaling Machine Learning
(ends 7:30 AM)
Expo Talk Panel:
Commerce Foundation Model
(ends )
Expo Talk Panel:
TikTok Symphony: AIGC Solution for Advertising
(ends 7:30 AM)
Expo Talk Panel:
Core Technical Interpretation and Best Practices of Responsible AI
(ends 7:30 AM)
Expo Talk Panel:
Compute: Past, Present & Future
(ends 7:30 AM)
7:30 a.m.
Registration (East & West)
(ends 6:00 PM)
9 a.m.
Creative AI Session 1 [9:00-9:03]
(ends 9:03 AM)
Break:
Coffee Break
(ends 10:00 AM)
9:30 a.m.
Tutorial:
Causality for Large Language Models
(ends 12:00 PM)
Tutorial:
Watermarking for Large Language Models
(ends 12:00 PM)
Tutorial:
Evaluating Large Language Models - Principles, Approaches, and Applications
(ends 12:00 PM)
Tutorial:
Opening the Language Model Pipeline: A Tutorial on Data Preparation, Model Training, and Adaptation
(ends 12:00 PM)
Tutorial:
Dynamic Sparsity in Machine Learning: Routing Information through Neural Pathways
(ends 12:00 PM)
Tutorial:
Experimental Design and Analysis for AI Researchers
(ends 12:00 PM)
Tutorial:
Flow Matching for Generative Modeling
(ends 12:00 PM)
10 a.m.
Expo Workshop:
Active Training: Building Agentic Apps with Llama 3.2 and Llama Stack
(ends 11:30 AM)
Expo Workshop:
Hands-On AI for Everyone using Jumping Jacks, Drones, and Your Favorite Soccer Players
(ends 11:30 AM)
Expo Workshop:
Accelerating Edge AI: Optimizing and Deploying AI Models with Qualcomm AI Hub
(ends 11:30 AM)
Expo Workshop:
Knowledge-enhanced LLMs for Industry Verticals
(ends 11:30 AM)
Expo Workshop:
Sony’s Efficient Content Creation and Editing through Deep Generative Models
(ends 11:30 AM)
Expo Workshop:
AutoGen 0.4: Redefining Agentic AI Systems
(ends 11:30 AM)
Expo Workshop:
Accelerating AI Research and Development with AMD Instinct Systems
(ends 11:30 AM)
Expo Workshop:
AutoGluon 1.2: Advancing AutoML with Foundational Models and LLM Agents
(ends 11:30 AM)
Expo Talk Panel:
Demystify Financial Textual Data with LLMs
(ends 11:00 AM)
noon
Expo Talk Panel:
Search & Classification: How AI Surveillance Policies Reduce Risk for the Financial Industry
(ends 1:00 PM)
Break:
Lunch Break
(ends 1:00 PM)
1 p.m.
Creative AI Session 2 [1:00-1:03]
(ends 1:03 PM)
Expo Demonstration:
Deploying Personal AI Assistants with Voice, LLMs, RAG via OpenVINO™ on the AI PC
(ends 3:00 PM)
Expo Demonstration:
MemoMagnet: A fridge-magnet memo agent based on LLM
(ends 3:00 PM)
Expo Demonstration:
HPC-AI.COM: Unleashing the Power of High-Performance Cloud Computing for Large-Scale AI Model Training
(ends 3:00 PM)
Expo Demonstration:
Augmenting Driving Scenes by High Fidelity Generative Models
(ends 3:00 PM)
Expo Demonstration:
Diffusion Video Editing on Mobile
(ends 3:00 PM)
Expo Demonstration:
Deploying Cached Conditional Mixture-of-Experts LLMs on Mobile Devices with Memory Constraints
(ends 3:00 PM)
Expo Demonstration:
Low-Rank Adaptation (LoRA) for Large Vision Model on a Mobile Device
(ends 3:00 PM)
Expo Demonstration:
Large Multimodal Model running on a mobile device
(ends 3:00 PM)
Expo Demonstration:
Video Ocean: Filmmaking for everyone
(ends 3:00 PM)
Expo Demonstration:
Automatically Deploying a Sequence-to-Sequence Transformer for Accelerated Discovery on the IBM HERMES Project Chip
(ends 3:00 PM)
Expo Demonstration:
EvalAssist - An LLM-as-a-Judge Framework
(ends 3:00 PM)
Expo Demonstration:
Site Reliability Engineering Agent-101 for Incident Management
(ends 3:00 PM)
Expo Demonstration:
ProLLM: Program analysis driven, LLM assisted application modernization
(ends 3:00 PM)
Expo Demonstration:
Software Engineering Agent-102
(ends 3:00 PM)
Expo Demonstration:
Moving beyond chat: Enabling LLMs with intrinsic functions that give fine-grained control in application development
(ends 3:00 PM)
Expo Demonstration:
IBM Granite Vision Model for Enterprise AI
(ends 3:00 PM)
Expo Demonstration:
Trace: An LLM-powered End-to-end Optimization Framework of AI Workflow
(ends 3:00 PM)
Expo Demonstration:
Practices of Alibaba Cloud PAI (Platform for AI): An AI Native Large Models and AIGC Engineering Platform
(ends 3:00 PM)
:
Video Ocean: Filmmaking for everyone
:
Diffusion Video Editing on Mobile
:
Automatically Deploying a Sequence-to-Sequence Transformer for Accelerated Discovery on the IBM HERMES Project Chip
:
Low-Rank Adaptation (LoRA) for Large Vision Model on a Mobile Device
:
Large Multimodal Model running on a mobile device
:
Deploying Personal AI Assistants with Voice, LLMs, RAG via OpenVINO™ on the AI PC
:
MemoMagnet: A fridge-magnet memo agent based on LLM
:
HPC-AI.COM: Unleashing the Power of High-Performance Cloud Computing for Large-Scale AI Model Training
:
Augmenting Driving Scenes by High Fidelity Generative Models
:
Deploying Cached Conditional Mixture-of-Experts LLMs on Mobile Devices with Memory Constraints
:
ProLLM: Program analysis driven, LLM assisted application modernization
:
IBM Granite Vision Model for Enterprise AI
:
Moving beyond chat: Enabling LLMs with intrinsic functions that give fine-grained control in application development
:
Trace: An LLM-powered End-to-end Optimization Framework of AI Workflow
:
Practices of Alibaba Cloud PAI (Platform for AI): An AI Native Large Models and AIGC Engineering Platform
:
EvalAssist - An LLM-as-a-Judge Framework
:
Software Engineering Agent-102
1:30 p.m.
Tutorial:
Beyond Decoding: Meta-Generation Algorithms for Large Language Models
(ends 4:00 PM)
Tutorial:
Out-of-Distribution Generalization: Shortcuts, Spuriousness, and Stability
(ends 4:00 PM)
Tutorial:
Generating Programmatic Solutions: Algorithms and Applications of Programmatic Reinforcement Learning and Code Generation
(ends 4:00 PM)
Tutorial:
Cross-disciplinary insights into alignment in humans and machines
(ends 4:00 PM)
Tutorial:
Advancing Data Selection for Foundation Models: From Heuristics to Principled Methods
(ends 4:00 PM)
Tutorial:
Sandbox for the Blackbox: How LLMs Learn Structured Data?
(ends 4:00 PM)
Tutorial:
PrivacyML: Meaningful Privacy-Preserving Machine Learning and How To Evaluate AI Privacy
(ends 4:00 PM)
2 p.m.
Expo Talk Panel:
Sequence Modeling in Financial Services
(ends )
Expo Talk Panel:
Improving Foundation Models Using Human Data
(ends 3:00 PM)
Expo Talk Panel:
Colossal-AI: Breakthroughs in Efficient AI Training and Implementation
(ends 3:00 PM)
Expo Talk Panel:
AgentInstruct: Agentic flows are effective synthetic-data generators
(ends 3:00 PM)
Expo Talk Panel:
Granite Time Series Foundation Models
(ends 3:00 PM)
Expo Talk Panel:
Graph Reasoning in Large Language Models
(ends 3:00 PM)
Expo Talk Panel:
Training the Unprecedented Decart Diffusion World Simulator at scale on the Crusoe Cluster
(ends 3:00 PM)
Expo Talk Panel:
Symbolic AI and Foundation Models Integration towards Reliable and Trustworthy Industry-grade AI Systems
(ends 3:00 PM)
4 p.m.
Break:
Coffee Break
(ends 4:30 PM)
5:30 p.m.
Invited Talk:
Invited Talk - Alison Gopnik
Alison Gopnik
(ends 6:15 PM)

WED 11 DEC
7:30 a.m.
Registration (East & West)
(ends 6:00 PM)
Break:
Coffee Break
(ends 8:30 AM)
8:30 a.m.
Invited Talk:
Invited Talk - Sepp Hochreiter
Sepp Hochreiter
(ends 9:30 AM)
9:30 a.m.
Break:
Coffee Break
(ends 10:00 AM)
10 a.m.
Oral Session 1A [10:00-11:00]
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes
NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction
(ends 11:00 AM)
Oral Session 1B [10:00-11:00]
Human Expertise in Algorithmic Prediction
RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
(ends 11:00 AM)
Oral Session 1C [10:00-11:00]
The Road Less Scheduled
Learning Diffusion at Lightspeed
Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity
(ends 11:00 AM)
Oral Session 1D [10:00-11:00]
Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure
Optimal Parallelization of Boosting
Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures
(ends 11:00 AM)
11 a.m.
Poster Session 1 [11:00-2:00]
Posters 11:00-2:00
Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context
Decoupled Kullback-Leibler Divergence Loss
Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval
DiffuPac: Contextual Mimicry in Adversarial Packets Generation via Diffusion Model
Federated Model Heterogeneous Matryoshka Representation Learning
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning
GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules
GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
How Far Can Transformers Reason? The Locality Barrier and Inductive Scratchpad
Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning
Learning symmetries via weight-sharing with doubly stochastic tensors
M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data
MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI
Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition
NaRCan: Natural Refined Canonical Image with Integration of Diffusion Prior for Video Editing
Online Bayesian Persuasion Without a Clue
Online Relational Inference for Evolving Multi-agent Interacting System
Quantifying the Gain in Weak-to-Strong Generalization
Self-Distilled Depth Refinement with Noisy Poisson Fusion
Separate and Reconstruct: Asymmetric Encoder-Decoder for Speech Separation
SpatialRGPT: Grounded Spatial Reasoning in Vision-Language Models
SustainDC: Benchmarking for Sustainable Data Center Control
SyncTweedies: A General Generative Framework Based on Synchronized Diffusions
The Value of Reward Lookahead in Reinforcement Learning
Unveiling the Power of Diffusion Features For Personalized Segmentation and Retrieval
WildPPG: A Real-World PPG Dataset of Long Continuous Recordings
$\textit{Trans-LoRA}$: towards data-free Transferable Parameter Efficient Finetuning
2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution
3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration
3D Gaussian Can Be Sparser Than You Thought: Efficient Rendering via Learned Fragment Pruning
3D Gaussian Splatting as Markov Chain Monte Carlo
3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs
4Diffusion: Multi-view Video Diffusion Model for 4D Generation
4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models
ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets
Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences
A Careful Examination of Large Language Model Performance on Grade School Arithmetic
Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling
Accelerating Inference with Fast and Expressive Sketch Structured Transform
Accelerating Pre-training of Multimodal LLMs via Chain-of-Sight
Accelerating Transformers with Spectrum-Preserving Token Merging
Accuracy is Not All You Need
Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures
A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
A Compositional Atlas for Algebraic Circuits
A Cross-Domain Benchmark for Active Learning
ActAnywhere: Subject-Aware Video Background Generation
Active Classification with Few Queries under Misspecification
Active design of two-photon holographic stimulation for identifying neural population dynamics
Active Learning of General Halfspaces: Label Queries vs Membership Queries
AdaFlow
AdaPKC: PeakConv with Adaptive Peak Receptive Field for Radar Semantic Segmentation
Adaptive Proximal Gradient Method for Convex Optimization
Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples
Adaptive Visual Scene Understanding: Incremental Scene Graph Generation
Ad Auctions for LLMs via Retrieval Augmented Generation
Addressing bias in online selection with limited budget of comparisons
Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation
A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health
AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
Advancing Video Anomaly Detection: A Concise Review and a New Dataset
A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks
Algebraic Positional Encodings
Algorithmic progress in language models
Aligning to Thousands of Varying Preferences via System Message Generalization
AllClear: A Comprehensive Dataset and Benchmark for Cloud Removal in Satellite Imagery
ALOHA: from Attention to Likes – a unified mOdel for understanding HumAn responses to diverse visual content
A Metalearned Neural Circuit for Nonparametric Bayesian Inference
A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes
An Analysis of Robustness of Non-Lipschitz Networks
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations
An Equivalence Between Static and Dynamic Regret Minimization
Animal-Bench: Benchmarking Multimodal Video Models for Animal-centric Video Understanding
AnonFair: A Flexible Toolkit for Algorithmic Fairness
ANT: Adaptive Noise Schedule for Time Series Diffusion Models
Any2Policy: Learning Visuomotor Policy with Any-Modality
Approximating mutual information of high-dimensional variables using learned representations
A Practitioner's Guide to Real-World Continual Multimodal Pretraining
A probability contrastive learning framework for 3D molecular representation learning
Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification
A Recipe for Charge Density Prediction
Are Graph Neural Networks Optimal Approximation Algorithms?
Artemis: Towards Referential Understanding in Complex Videos
Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning
A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $\Theta(T^{2/3})$ and its Application to Best-of-Both-Worlds
A Simple and Optimal Approach for Universal Online Learning with Gradient Variations
A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data
A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation
A teacher-teacher framework for clinical language representation learning
A Trajectory-aware Spatio-temporal Graph for Video Salient Object Ranking
Attack-Resilient Image Watermarking Using Stable Diffusion
A two-scale Complexity Measure for Deep Learning Models
AutoCV: Empowering Reasoning with Automated Process Labeling via Confidence Variation
Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents
Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs
Automated Multi-level Preference for MLLMs
Automatic Outlier Rectification via Optimal Transport
Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models
AverNet: All-in-one Video Restoration for Time-varying Unknown Degradations
A Versatile Diffusion Transformer with Mixture of Noise Levels for Audiovisual Generation
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation
BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack
Bayesian Adaptive Calibration and Optimal Design
Bayesian Identification of the Hamiltonian Inductive Bias in Dynamical Systems
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization
Bayes-optimal learning of an extensive-width neural network from quadratically many samples
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Foundation Models
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
Benchmarking Counterfactual Image Generation
Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming
Benchmarking the Reasoning Robustness against Noisy Rationales in Chain-of-thought Prompting
BenchMARL: Benchmarking Multi-Agent Reinforcement Learning
Beware of Road Markings: A New Adversarial Patch Attack to Monocular Depth Estimation
Beyond Optimism: Exploration With Partially Observable Rewards
Beyond Slow Signs in High-fidelity Model Extraction
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
Blind Image Restoration via Fast Diffusion Inversion
B'MOJO: Realizations of Hybrid State Space Models with Eidetic and Fading Memory
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models
Boosting Transferability and Discriminability for Time Series Domain Adaptation
Bootstrapping Top-down Information for Self-modulating Slot Attention
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking
Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model
Breaking the curse of dimensionality in structured density estimation
Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack
Bridging 3D Scene and Large Language Models with Object Identifiers
Bridging OOD Generalization and Detection: A Graph-Theoretic View
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers
CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset
Can LLMs Solve Molecule Puzzles? A Multimodal Benchmark for Molecular Structure Elucidation
CAPE: Context-Adaptive Positional Encoding for Length Extrapolation
Categorical Flow Matching on Statistical Manifolds
Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing
Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs
Classification Diffusion Models: Revitalizing Density Ratio Estimation
Clustering with Non-adaptive Subset Queries
CODA: A Correlation-Oriented Disentanglement and Augmentation Modeling Scheme for Better Resisting Subpopulation Shifts
Code Agents are State of the Art Software Testers
CoFie: Learning Compact Neural Surface Representations with Coordinate Fields
Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models
Coherent 3D Scene Diffusion From a Single RGB Image
Collaborative Video Diffusion: Consistent Multi-video Generation with Camera Control
Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
Comprehensive Framework for Curating Speech Datasets and Evaluating ASR Systems: A Case Study for the Polish Language
Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise
Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
Conditional Density Estimation with Histogram Trees
Confidence Calibration of Classifiers with Many Classes
Conformalized Credal Set Predictors
Conformalized Time Series with Semantic Features
Conjugate Bayesian Two-step Change Point Detection for Hawkes Process
Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning
Consensus Learning with Deep Sets for Essential Matrix Estimation
Constrained Diffusion Models via Dual Training
Constructing Semantics-Aware Adversarial Examples with Probabilistic Perspective
ContextCite: Attributing Model Generation to Context
Contextual Multinomial Logit Bandits with General Value Functions
Continual Audio-Visual Sound Separation
Continuous Temporal Domain Generalization
Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets
ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence
Cooperate or Collapse: Emergence of Sustainability in a Society of LLM Agents
Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Coupled Mamba: Enhanced Multimodal Fusion with Coupled State Space Model
Credal Deep Ensembles for Uncertainty Quantification
Cross-Device Collaborative Test-Time Adaptation
CryoBench: Datasets and Benchmarks for Heterogeneous Cryo-EM Reconstruction
DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA
DASH: Warm-Starting Neural Network Training Without Loss of Plasticity Under Stationarity
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum
DAVED: Data Acquisition via Experimental Design for Data Markets
Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL
Deep Correlated Prompting for Visual Recognition with Missing Modalities
DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection
Deep Homomorphism Networks
Déjà Vu Memorization in Vision–Language Models
DeltaDEQ: Exploiting Heterogeneous Convergence for Accelerating Deep Equilibrium Iterations
Demographic parity fair regression in unaware setting
Denoising Diffusion Path: Attribution Noise Reduction with An Auxiliary Diffusion Model
Dense Connector for MLLMs
Derivative-enhanced Deep Operator Network
Derivatives of Stochastic Gradient Descent
DetectEval: Benchmarking LLM-Generated Text Detection in Real-World Scenarios
Deterministic Policies for Constrained Reinforcement Learning in Polynomial-Time
Diffeomorphic interpolation for efficient persistence-based topological optimization
Differentiable Quantum Computing for Large-scale Linear Control
Differentially Private Set Representations
DiffGS: Functional Gaussian Splatting Diffusion
Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection
Diffusion of Thought: Chain-of-Thought Reasoning in Diffusion Language Models
Diffusion-Reward Adversarial Imitation Learning
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function
DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation
DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models
DisC-GS: Discontinuity-aware Gaussian Splatting
Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning
Disentangling Interpretable Factors of Variations with Supervised Independent Subspace Principal Component Analysis
Distributed Least Squares in Small Space via Sketching and Bias Reduction
Distributional Preference Alignment of LLMs via Optimal Transport
DiTFastAtten: Accelerate Diffusion Transformers Through Efficient Attention Computation
DivSafe: Evaluating the Generalization of LLM Safety Training Across Diverse Tasks and Prompt Types
DMesh: A Differentiable Mesh Representation
Do CLIP Models Always Generalize Better than ImageNet Models?
Doubly Mild Generalization for Offline Reinforcement Learning
DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM
DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation
DreamScene: Layout-Guided 3D Scene Generation
Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data
DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model
DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs
Dual Critic Reinforcement Learning under Partial Observability
Dual-Personalizing Adapter for Federated Foundation Models
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models
Dynamic Multi-Object 3D Grounding with Language Informed Spatial Attention
EASI: Evolutionary Adversarial Simulator Identification for Sim-to-Real Transfer
Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting
Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously
EfficientCAPER: An End-to-End Framework for Fast and Robust Category-Level Articulated Object Pose Estimation
Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning
Efficient Graph Matching for Correlated Stochastic Block Models
Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms
Efficient Zero-Shot HOI Detection: Enhancing VLM Adaptation with Innovative Prompt Learning
EgoChoir: Capturing 3D Human-Object Interaction Regions from Egocentric Views
EGonc : Energy-based Open-Set Node Classification with substitute Unknowns
Einsum Benchmark: Enabling the Development of Next-Generation Tensor Execution Engines
emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography
Empowering Visible-Infrared Person Re-Identification with Large Foundation Models
Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces
Enhancing Protein Mutation Effect Prediction through a Retrieval-Augmented Framework
Entropy Coding of Large Unordered Data Structures
Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning
Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation
Equivariant Flow-Matching for Molecular Conformer Generation
Equivariant spatio-hemispherical networks for diffusion MRI deconvolution
Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation
Estimating Ego-Body Pose from Doubly Sparse Egocentric Video Data
Estimating Fréchet bounds for validating programmatic weak supervision
E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding
Euclidean distance compression via deep random features
Evaluating alignment between humans and neural network representations in image-based learning tasks
Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads
Evaluating the design space of diffusion-based generative models
Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity
Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization
Exploiting Descriptive Completeness Prior for Cross Modal Hashing with Incomplete Labels
Exploration by Learning Diverse Skills through Successor State Measures
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation
Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning
Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces
FairJob: A Real-World Dataset for Fairness in Online Systems
Fairness without Harm: An Influence-Guided Active Sampling Approach
Fair Secretaries with Unfair Predictions
FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification
Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification
Fast Proxy Experiment Design for Causal Effect Identification
Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning
FinBen: An Holistic Financial Benchmark for Large Language Models
FineCLIP: Self-distilled Region-based CLIP for Better Fine-Grained Understanding
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
Fishers and Hessians of Continuous Relaxations
(FL)${}^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
Flexible mapping of abstract domains by grid cells via self-supervised extraction and projection of generalized velocity signals
F-OAL: Foward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning
FreeSplat: Generalizable 3D Gaussian Splatting Towards Free View Synthesis of Indoor Scenes
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models
Full-Atom Peptide Design with Geometric Latent Diffusion
Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models
Game-Traversal-Benchmark: Evaluating Planning Abilities Of Large Language Models Via Traversing 2D Game Maps
GC-Bench: An Open and Unified Benchmark for Graph Condensation
Generalization Beyond Data Imbalance: A Controlled Study on CLIP for Transferable Insights
Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure
Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization
Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling
Generative Hierarchical Materials Search
Generative Modeling of Molecular Dynamics Trajectories
GFlowNet Assisted Biological Sequence Editing
Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems
Gorilla: Teaching LLMs to Use Tools
Graphcode: Learning from multiparameter persistent homology using graph neural networks
Graph Neural Networks and Arithmetic Circuits
Graph Neural Networks Do Not Always Oversmooth
GraphVis: Boosting LLMs with Visual Knowledge Graph Integration
Great Minds Think Alike: The Universal Convergence Trend of Input Salience
Group-wise oracle-efficient algorithms for online multi-group learning
GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring
GSDF: 3DGS Meets SDF for Improved Neural Rendering and Reconstruction
GS-Hider: Hiding Messages into 3D Gaussian Splatting
GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks
Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization
Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame
HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach
Harnessing Multiple Correlated Networks for Exact Community Recovery
HAWK: Learning to Understand Open-World Video Anomalies
HEALNet: Multimodal Fusion for Heterogeneous Biomedical Data
HEST-1k: A Dataset For Spatial Transcriptomics and Histology Image Analysis
Hierarchical Selective Classification
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
High Rank Path Development: an approach of learning the filtration of stochastic processes
High-Resolution Image Harmonization with Adaptive-Interval Color Transformation
Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation
Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models
How does Gradient Descent Learn Features --- A Local Analysis for Regularized Two-Layer Neural Networks
How In-Context Learning Emerges from Training on Unstructured Data: The Role of Co-Occurrence, Positional Information, and Noise Structures
How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval
Human Expertise in Algorithmic Prediction
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models
Hybrid Global Causal Discovery with Local Search
Hybrid Mamba: An Promising In-Context RL for Long-Term Decision
Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
IF-Font: Ideographic Description Sequence-Following Font Generation
Implicit Curriculum in Procgen Made Explicit
Improved Analysis for Bandit Learning in Matching Markets
Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
Improved Generation of Adversarial Examples Against Safety-aligned LLMs
Improved Guarantees for Fully Dynamic $k$-Center Clustering with Outliers in General Metric Spaces
Improved learning rates in multi-unit uniform price auctions
Improving Generalization of Dynamic Graph Learning via Environment Prompt
Improving robustness to corruptions with multiplicative weight perturbations
Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization
Inference of Neural Dynamics Using Switching Recurrent Neural Networks
Inferring stochastic low-rank recurrent neural networks from neural data
Infinite-Dimensional Feature Interaction
Information Re-Organization Improves Reasoning in Large Language Models
Information-theoretic Generalization Analysis for Expected Calibration Error
Initialization is Critical to Whether Transformers Fit Composite Functions by Inference or Memorizing
Instance-adaptive Zero-shot Chain-of-Thought Prompting
Integrating Paralinguistics in Speech-Empowered Large Language Models for Natural Conversation
Integrating Suboptimal Human Knowledge with Hierarchical Reinforcement Learning for Large-Scale Multiagent Systems
Interpretable Image Classification with Adaptive Prototype-based Vision Transformers
Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors
Invariant Tokenization for Language Model Enabled Crystal Materials Generation
Inversion-based Latent Bayesian Optimization
IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs
Is Score Matching Suitable for Estimating Point Processes?
Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval
Iterative Methods via Locally Evolving Set Process
Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking
Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization
LACIE: Listener-Aware Finetuning for Calibration in Large Language Models
Language Models as Hierarchy Encoders
Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning
Large Language Model Unlearning via Embedding-Corrupted Prompts
Large language model validity via enhanced conformal prediction methods
Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization
LaSe-E2V: Towards Language-guided Semantic-Aware Event-to-Video Reconstruction
Latent Diffusion for Neural Spiking Data
Latent Learning Progress Drives Autonomous Goal Selection in Human Reinforcement Learning
LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling
Learning 1D Causal Visual Representation with De-focus Attention Networks
Learning 3D Equivariant Implicit Function with Patch-Level Pose-Invariant Representation
Learning Action and Reasoning-Centric Image Editing from Videos and Simulation
Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification
Learning Cortico-Muscular Dependence through Orthonormal Decomposition of Density Ratios
Learning Diffusion at Lightspeed
Learning Diffusion Priors from Observations by Expectation Maximization
Learning diverse causally emergent representations from time series data
Learning from Offline Foundation Features with Tensor Augmentations
Learning from Snapshots of Discrete and Continuous Data Streams
Learning Heuristics for Numeric Planning
Learning high-dimensional targets by two-parameter models and gradient flow
Learning Hybrid Models for Digital Twins of Dynamical Systems
Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems
Learning Infinitesimal Generators of Continuous Symmetries from Data
Learning Optimal Lattice Vector Quantizers for End-to-end DNN Image Compression
Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation
Learning Scene-specific Descriptions via Adaptive Renormalization for Open-vocabulary Scene Graph Generation
Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
Learning to Handle Complex Constraints for Vehicle Routing Problems
Learning Where to Edit Vision Transformers
Leveraging partial stragglers within gradient coding
Leveraging Visual Tokens for Extended Text Contexts in Multi-Modal Learning
Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering for HDR View Synthesis
Likelihood-based differentiable structure learning
Linear Causal Representation Learning from Unknown Multi-node Interventions
Linear Regression using Heterogeneous Data Batches
Linear Transformers are Versatile In-Context Learners
Linear Uncertainty Quantification of Graphical Model Inference
LION: Linear Group RNN for 3D Object Detection in Point Clouds
LiT: Unifying LiDAR "Languages" with LiDAR Translator
LLM-AutoDA: Large Language Model-Driven Automatic Data Augmentation for Long-tailed Problems
LLM-based Skill Diffusion for Zero-shot Policy Adaptation
LLM-Check: Investigating Detection of Hallucinations in Large Language Models
LLM Circuit Analyses Are Consistent Across Training and Scale
LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation
LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model
Local Curvature Smoothing with Stein's Identity for Efficient Score Matching
Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk
Logical characterizations of recurrent graph neural networks with reals and floats
LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
LP-3DGS: Learning to Prune 3D Gaussian Splatting
LRM-Zero: Training Large Reconstruction Models with Synthesized Data
LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing
Lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers
MADiff: Offline Multi-agent Learning with Diffusion Models
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
Make Fashion Real: Texture-preserving Rendered-to-Real Translation with Diffusion Models
Marginal Causal Flows for Validation and Inference
MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learning
MC-DiT: Contextual Enhancement via Clean-to-Clean Reconstruction for Masked Diffusion Models
Measuring Dejavu Memorization Efficiently
Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration
Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence
Memorize What Matters: Emergent Scene Decomposition from Multitraverse
Memory-Efficient LLM Training with Online Subspace Descent
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
Microstructures and Accuracy of Graph Recall by Large Language Models
Minimizing Hyperspherical Energy for Diverse Deep Ensembling
Mitigating Biases in Blackbox Feature Extractors for Image Classification Tasks
Mitigating Object Hallucination via Concentric Causal Attention
Mitigating Spurious Correlations via Disagreement Probability
Mixture of Link Predictors on Graphs
MmCows: A Multimodal Dataset for Dairy Cattle Monitoring
MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations
MMSite: A Multi-modal Framework for the Identification of Active Sites in Proteins
Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models
Model-based Diffusion for Trajectory Optimization
Model Based Inference of Synaptic Plasticity Rules
Molecule Generation with Fragment Retrieval Augmentation
MoMu-Diffusion: On Learning Long-Term Motion-Music Synchronization and Correspondence
Monoculture in Matching Markets
Monte Carlo Tree Search based Space Transfer for Black Box Optimization
Motif-oriented influence maximization for viral marketing in large-scale social networks
MotionBooth: Motion-Aware Customized Text-to-Video Generation
Motion Generation based on Spatial-Temporal Joint Modeling
Motion Graph Unleashed: A Novel Approach to Video Prediction
MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting
Multi-Agent Coordination via Multi-Level Communication
Multi-Chain Graphs of Graphs: A New Paradigm in Blockchain Dataset
Multi-language Diversity Benefits Autoformalization
Multimodal Conformal Prediction in Dynamic Environments
Multiple Physics Pretraining for Spatiotemporal Surrogate Models
Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs
Multi-Winner Reconfiguration
MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering
Mutli-Armed Bandits with Network Interference
MVGamba: Unify 3D Content Generation as State Space Sequence Modeling
NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples
Navigating Chemical Space with Latent Flows
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models
Near-Optimal Distributionally Robust RL with General $L_p$ Norms
Near-Optimal Methods for Convex Simple Bilevel Problems
Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD
Neglected Hessian component explains mysteries in sharpness regularization
NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation
Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms
Neural Krylov Iteration for Accelerating Linear System Solving
Neural Model Checking
Neural Residual Diffusion Models for Deep Scalable Vision Generation
NeuralSteiner: Learning Steiner Tree for Overflow-avoiding Global Routing in Chip Design
NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction
Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
No Filter: Towards Cultural and Socioeconomic Diversity in Multimodal Systems
Noisy Dual Mirror Descent: A Near Optimal Algorithm for Jointly-DP Convex Resource Allocation
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation
Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset
Nonstationary Sparse Spectral Permanental Process
No-regret Bandit Exploration based on Soft Tree Ensemble Model
No-Regret Learning for Fair Multi-Agent Social Welfare Optimization
No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting
No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance
NVRC: Neural Video Representation Compression
Offline Multitask Representation Learning for Reinforcement Learning
OMG-LLaVA: Bridging Image-level, Object-level, Pixel-level Reasoning and Understanding
On Complexity of Teaching a Family of Linear Behavior Cloning Learners
One-Step Diffusion Distillation through Score Implicit Matching
One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos
Online Weighted Paging with Unknown Weights
On the cohesion and separability of average-link for hierarchical agglomerative clustering
On the Comparison between Multi-modal and Single-modal Contrastive Learning
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
On the Identifiability of Hybrid Physics-Neural Models: Meta-Learning as a Solution
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice
On the Saturation Effects of Spectral Algorithms in Large Dimensions
Opponent Modeling based on Subgoal Inference
Optimal and Approximate Adaptive Stochastic Quantization
Optimal Multiclass U-Calibration Error and Beyond
Optimal Parallelization of Boosting
Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL
Optimistic Verifiable Training by Controlling Hardware Nondeterminism
Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport
Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition
PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher
pcaGAN: Improving Posterior-Sampling cGANs via Principal Component Regularization
Perceptual Fairness in Image Restoration
PERIA: Perceive, Reason, Imagine, Act via Holistic Language and Vision Planning for Manipulation
pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning
Physics-Guided Neural Impulse Response Field via Implicit Wave Propagation Modeling
Physics-Informed Variational State-Space Gaussian Processes
Piecewise deterministic generative models
POCA: Partially Observable Cost-Aware Active-Learning
Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning
Policy Optimization for Robust Average Reward MDPs
Poseidon: Efficient Foundation Models for PDEs
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice
Preferential Normalizing Flows
PrefPaint: Aligning Image Inpainting Diffusion Model with Human Preference
Pre-trained Gaussian Processes for Bayesian Optimization
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
Probabilistic Conformal Distillation for Enhancing Missing Modality Robustness
Probabilistic size-and-shape functional mixed models
Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
Probing the Decision Boundaries of In-context Learning in Large Language Models
PRODuctive bandits: Importance Weighting No More
Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions
Prospective Representation Learning for Non-Exemplar Class-Incremental Learning
Provable Benefits of Complex Parameterizations for Structured State Space Models
Proving Theorems Recursively
Pseudo-Private Data Guided Model Inversion Attacks
Quantum algorithm for large-scale market equilibrium computation
QVAE-Mole: The Quantum VAE with Spherical Latent Variable Learning for 3-D Molecule Generation
RAGraph: A General Retrieval-Augmented Graph Learning Framework
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
Random Subgraph Detection Using Queries
RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning
RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models
Real-Time Recurrent Learning using Trace Units in Reinforcement Learning
Reasoning Multi-Agent Behavioral Topology for Interactive Autonomous Driving
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training
Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents
Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity
RedPajama: an Open Dataset for Training Large Language Models
REDUCR: Robust Data Downsampling using Class Priority Reweighting
RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance
Referring Human Pose and Mask Estimation In the Wild
ReFIR: Grounding Large Restoration Models with Retrieval Augmentation
Refusal in Language Models Is Mediated by a Single Direction
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
ReGS: Reference-based Controllable Scene Stylization with Gaussian Splatting
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment
Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity
Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising
Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
Reparameterization invariance in approximate Bayesian inference
Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling
Reproducibility study of FairAC
Reproducibility study of “LICO: Explainable Models with Language-Image Consistency"
Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design
[Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework"
Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual Noise
Resolving Partial Observability in Decision Processes via the Lambda Discrepancy
Rethinking Decoders for Transformer-based Semantic Segmentation: Compression is All You Need
Rethinking LLM Memorization through the Lens of Adversarial Compression
Rethinking Optimal Transport in Offline Reinforcement Learning
Rethinking the Capacity of Graph Neural Networks for Branching Strategy
Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data
Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference
RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation
ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization
Robot Policy Learning with Temporal Optiaml Transport Reward
ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions
SafeWorld: Geo-Diverse Safety Alignment
SAM-Guided Masked Token Prediction for 3D Scene Understanding
Sample Complexity of Interventional Causal Representation Learning
Satformer: Accurate and Robust Traffic Data Estimation for Satellite Networks
Scalable DBSCAN with Random Projections
Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes
Scaling Law for Time Series Forecasting
Scaling Laws and Compute-Optimal Training without Fixed Training Duration
Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore
SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models
SE(3)-bi-equivariant Transformers for Point Cloud Assembly
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
SeeClear: Semantic Distillation Enhances Pixel Condensation for Video Super-Resolution
Selective Explanations
Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences
Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation
Semantics and Spatiality of Emergent Communication
SemCoder: Training Code Language Models with Comprehensive Semantics
Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting
Semi-Truths: A Large-Scale Dataset for Testing Robustness of AI-Generated Image Detectors
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
Sequoia: Scalable and Robust Speculative Decoding
SfPUEL: Shape from Polarization under Unknown Environment Light
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions
Sharpness-Aware Minimization Activated Interactive Teaching Understanding and Optimization
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood
SHDocs: A dataset, benchmark, and method to efficiently generate high-quality, real-world specular highlight data with near-perfect alignment
SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models
ShowMaker: Creating High-Fidelity 2D Human Video via Fine-Grained Diffusion Modeling
Simplified and Generalized Masked Diffusion for Discrete Data
SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion
Single Image Reflection Separation via Interactive Dual-Stream Transformers
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
Soft Superpixel Neighborhood Attention
SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-situ Observations for Large-scale Solar Energy Forecasting
SpaceByte: Towards Deleting Tokenization from Large Language Modeling
SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead
Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis
Spectral Adapter: Fine-Tuning in Spectral Space
Spectral Graph Pruning Against Over-Squashing and Over-Smoothing
SpeechAlign: Speech Language Models Can Self-Improve via Preference Optimization
SpeechForensics: Audio-Visual Speech Representation Learning for Face Forgery Detection
Speeding up non-parametric regression via distribution compression
SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network
Spiking Token Mixer: A event-driven friendly Former structure for spiking neural networks
SPO: Sequential Monte Carlo Policy Optimisation
SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning
SRFUND: A Multi-Granularity Hierarchical Structure Reconstruction Benchmark in Form Understanding
Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics
START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation
State-free Reinforcement Learning
State Space Models on Temporal Graphs: A First-Principles Study
Statistical-Computational Trade-offs for Density Estimation
Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
Stepping on the Edge: Curvature Aware Learning Rate Tuners
Stepwise Alignment for Constrained Language Model Policy Optimization
Stochastic contextual bandits with graph feedback: from independence number to MAS number
Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements
Strategic Littlestone Dimension: Improved Bounds on Online Strategic Classification
Stratified Prediction-Powered Inference for Effective Hybrid Evaluation of Language Models
Stress-Testing Capability Elicitation With Password-Locked Models
Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack
"Studying How to Efficiently and Effectively Guide Models with Explanations" - A Reproducibility Study
Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning
Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
Synergistic Dual Spatial-aware Generation of Image-to-text and Text-to-image
Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation
Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces
Taming Generative Diffusion Prior for Universal Blind Image Restoration
TAPTRv2: Tracking Any Point with Transformers as Detection
Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings
Temporal Sentence Grounding with Relevance Feedback in Videos
Test-time Aggregation for Collaborative Filtering
Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction
Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models
Text to Blind Motion
The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
The Many Faces of Optimal Weak-to-Strong Learning
The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks
Theoretical guarantees in KL for Diffusion Flow Matching
Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning
The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models
The Price of Implicit Bias in Adversarially Robust Generalization
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models
The Road Less Scheduled
The Star Geometry of Critic-Based Regularizer Learning
The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models
Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
To Believe or Not to Believe Your LLM
To Learn or Not to Learn, That is the Question
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Toward a Stable, Fair, and Comprehensive Evaluation of Object Hallucination in Large Vision-Language Models
Toward a Well-Calibrated Discrimination via Survival Outcome-Aware Contrastive Learning
Toward Robust Incomplete Multimodal Sentiment Analysis via Representation Factorization and Alignment
Towards Accurate and Fair Cognitive Diagnosis via Monotonic Data Augmentation
Towards a Scalable Reference-Free Evaluation of Generative Models
Towards Croppable Implicit Neural Representations
Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration
Towards Effective Planning Strategies for Dynamic Opinion Networks
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Towards Exact Gradient-based Training on Analog In-memory Computing
Towards Flexible Visual Relationship Segmentation
Towards General Conceptual Model Editing via Adversarial Representation Engineering
Towards Human-AI Complementarity with Predictions Sets
Towards Multi-Domain Learning for Generalizable Video Anomaly Detection
Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases
Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens
Towards Understanding the Mechanisms of Associative Memory in Transformers
Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes
Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis
Training for Stable Explanation for Free
Trajectory Diffusion for ObjectGoal Navigation
Transductive Active Learning: Theory and Applications
Transferable Adversarial Attacks on SAM and Its Downstream Models via Universal Meta Initialization and Gradient Robust Attacks
Transformers are Minimax Optimal Nonparametric In-Context Learners
Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness
Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees
TripletCLIP: Improving Compositional Reasoning of CLIP via Vision-Language Negatives
Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging
UDPM: Upsampling Diffusion Probabilistic Models
UltraEdit: Instruction-based Fine-Grained Image Editing at Scale
UMB: Understanding Model Behavior for Open-World Object Detection
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure
Understanding Preference Learning Through the Lens of Coverage
Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
Understanding the Transferability of Representations via Task-Relatedness
Understanding Transformer Reasoning Capabilities via Graph Algorithms
Unified Covariate Adjustment for Causal Inference
Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
Unified Lexical Representation for Interpretable Visual-Language Alignment
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification
Unifying Homophily and Heterophily for Spectral Graph Neural Networks via Triple Filter Ensembles
UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-Classes
Unitary Convolutions for Learning on Graphs and Groups
Unlocking the Capabilities of Masked Generative Models for Image Synthesis via Self-Guidance
Unmasking the Veil: An Investigation into Concept Ablation for Privacy and Copyright Protection in Images
Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation
USCILab3D: A Large-scale, Long-term, Semantically Annotated Outdoor Dataset
Vaccine: Perturbation-aware Alignment for Large Language Models Finetuning
Validating Climate Models with Spherical Convolutional Wasserstein Distance
Variational Flow Matching for Graph Generation
VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding
Verified Code Transpilation with LLMs
Verified Safe Reinforcement Learning for Neural Network Dynamic Models
VeXKD: The Versatile Integration of Cross-Modal Fusion and Knowledge Distillation for 3D Perception
VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models
Vidu4D: Single Generated Video to High-Fidelity 4D Reconstruction with Dynamic Gaussian Surfels
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning
Visual Perception by Large Language Model’s Weights
VMamba: Visual State Space Model
Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection
VQ-Map: Bird's-Eye-View Map Layout Estimation in Tokenized Discrete Space via Vector Quantization
Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models
What do Graph Neural Networks learn? Insights from Tropical Geometry
What makes unlearning hard and what to do about it
What matters when building vision-language models?
When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
Where does In-context Learning \\ Happen in Large Language Models?
Why are Visually-Grounded Language Models Bad at Image Classification?
Wings: Learning Multimodal LLMs without Text-only Forgetting
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation
X-Ray: A Sequential 3D Representation For Generation
You May Better Reconstruct Anomalous over Normal Graphs: Analysis and a Simple Method for Reconstruction-based Graph-Level Anomaly Detection
ZeroMark: Towards Dataset Ownership Verification without Disclosing Dataset-specified Watermarks
Zero-shot Image Editing with Reference Imitation
Zero-Shot Transfer of Neural ODEs
ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification
ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination
(ends 2:00 PM)
Creative AI Session 3 [11:00-11:03]
(ends 11:03 AM)
Expo Talk Panel:
Deep tabular data
(ends 12:00 PM)
Expo Talk Panel:
Industrial Applications of Distributional Preference Alignment of LLMs via Optimal Transport
(ends 12:00 PM)
Expo Workshop:
Open-Sora: Democratizing Efficient Video Production for All
(ends 12:30 PM)
Expo Workshop:
AI for Enhanced Spacecraft Orientation
(ends 12:30 PM)
Expo Workshop:
Streamlining Computer Vision Data Annotation with Segment Anything 2.1
(ends 12:30 PM)
Expo Workshop:
Post-training LLMs: From Algorithms to Training Infrastructures
(ends 12:30 PM)
1 p.m.
Break:
Lunch Break
(ends 2:30 PM)
2:30 p.m.
Expo Talk Panel:
Empirical Rigor at Scale – or, How Not to Fool Yourself
(ends 3:30 PM)
Expo Talk Panel:
Can AI Save Us From Ourselves? Generative AI and Content Moderation
(ends 3:30 PM)
Expo Talk Panel:
Mastering Distributed Training: Best Practices for Scalable Model Training
(ends 3:30 PM)
Expo Talk Panel:
MegaBeam-Mistral-7B: Advancing Long-Context Processing for Real-World AI Applications
(ends 3:30 PM)
Invited Talk:
Invited Talk - FeiFei Li
Li Fei-Fei
(ends 3:30 PM)
Expo Talk Panel:
Learnings From Teams Training Large-Scale Models: Challenges and Solutions for Monitoring at Hyperscale
(ends 3:30 PM)
3:30 p.m.
Oral Session 2A [3:30-4:30]
Enhancing Preference-based Linear Bandits via Human Response Time
Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making
AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents
(ends 4:30 PM)
Oral Session 2B [3:30-4:30]
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
The Sample-Communication Complexity Trade-off in Federated Q-Learning
Understanding, Rehearsing, and Introspecting: Learn a Policy from Textual Tutorial Books in Football Games
(ends 4:30 PM)
Oral Session 2C [3:30-4:30]
RL-GPT: Integrating Reinforcement Learning and Code-as-policy
Statistical Efficiency of Distributional Temporal Difference
SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling
(ends 4:30 PM)
Oral Session 2D [3:30-4:30]
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
(ends 4:30 PM)
4:30 p.m.
Poster Session 2 [4:30-7:30]
Posters 4:30-7:30
Asynchronous Perception Machine for Test Time Training
Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication
Belief-State Query Policies for Planning With Preferences Under Partial Observability
Collaboration! Towards Robust Neural Methods for Routing Problems
Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
Credit Attribution and Stable Compression
DDR: Exploiting Deep Degradation Response as Flexible Image Descriptor
Dendritic Integration Inspired Artificial Neural Networks Enhance Data Correlation
EMR-Merging: Tuning-Free High-Performance Model Merging
Generative Fractional Diffusion Models
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)
Pessimistic Backward Policy for GFlowNets
Provably Optimal Memory Capacity for Modern Hopfield Models
Reinforcement Learning with Lookahead Information
Rejection via Learning Density Ratios
Why Warmup the Learning Rate? Underlying Mechanisms and Improvements
$\texttt{dattri}$: A Library for Efficient Data Attribution
3DET-Mamba: Causal Sequence Modelling for End-to-End 3D Object Detection
3DGS-Enhancer: Enhancing Unbounded 3D Gaussian Splatting with View-consistent 2D Diffusion Priors
4+3 Phases of Compute-Optimal Neural Scaling Laws
A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers
A Canonization Perspective on Invariant and Equivariant Learning
Accelerating Best-of-N via Speculative Rejection
ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
Achieving Domain-Independent Certified Robustness via Knowledge Continuity
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
A Closer Look at AUROC and AUPRC under Class Imbalance
A Closer Look at Deep Learning Phenomena Through A Telescoping Lens
A Concept-Based Explainability Framework for Large Multimodal Models
A Consistency-Aware Spot-Guided Transformer for Versatile and Hierarchical Point Cloud Registration
ActionAtlas: A VideoQA Benchmark for Fine-grained Action Recognition
Adam with model exponential moving average is effective for nonconvex optimization
Adaptable Logical Control for Large Language Models
Adaptive Experimentation When You Can't Experiment
AdaptiveISP: Learning an Adaptive Image Signal Processor for Object Detection
Adaptive Sampling for Efficient Softmax Approximation
Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
Advancing Spiking Neural Networks for Sequential Modeling through Central Pattern Generators
Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation
A Generative Approach to Control Complex Physical Systems
AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents
Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction
A Gradient Accumulation Method for Dense Retriever under Memory Constraint
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy
AirSketch: Generative Motion to Sketch
A Large-Scale Human-Centric Benchmark for Referring Expression Comprehension in the LMM Era
Algorithmic Capabilities of Random Transformers
Aligning Audio-Visual Joint Representations with an Agentic Workflow
Aligning Diffusion Models by Optimizing Human Utility
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem
Alleviate Anchor-Shift: Explore Blind Spots with Cross-View Reconstruction for Incomplete Multi-View Clustering
Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits
A Locally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization
A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs
A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
Amortized Active Causal Induction with Deep Reinforcement Learning
Amortized Eigendecomposition for Neural Networks
An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints
An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations
An Improved Empirical Fisher Approximation for Natural Gradient Descent
An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
A Novel Approach to Loss Landscape Characterization without Over-Parametrization
Approximately Equivariant Neural Processes
Approximation-Aware Bayesian Optimization
A Rank-Based Metric for Evaluating Large Language Models
Arboretum: A Large Multimodal Dataset Enabling AI for Biodiversity
ARC: A Generalist Graph Anomaly Detector with In-Context Learning
Are nuclear masks all you need for improved out-of-domain generalization? A closer look at cancer classification in histopathology.
Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections
A robust inlier identification algorithm for point cloud registration via $\mathbf{\ell_0}$-minimization
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation
AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction
Association of Objects May Engender Stereotypes: Mitigating Association-Engendered Stereotypes in Text-to-Image Generation
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning
A Theoretical Perspective for Speculative Decoding Algorithm
A Unifying Normative Framework of Decision Confidence
Autobidder's Dilemma: Why More Sophisticated Autobidders Lead to Worse Auction Efficiency
Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistency
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
Average gradient outer product as a mechanism for deep neural collapse
Balancing Context Length and Mixing Times for Reinforcement Learning at Scale
Balancing Multimodal Learning with Classifier-guided Gradient Modulation
BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts
Bandits with Abstention under Expert Advice
B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data
Base of RoPE Bounds Context Length
Batched Energy-Entropy acquisition for Bayesian Optimization
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
BEACON: Benchmark for Comprehensive RNA Tasks and Language Models
BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
Benchmarking LLMs via Uncertainty Quantification
BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays
Beyond Single Stationary Policies: Meta-Task Players as Naturally Superior Collaborators
Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps
Biologically-Motivated Learning Model for Instructed Visual Processing
BitDelta: Your Fine-Tune May Only Be Worth One Bit
BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference
BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages
Block Sparse Bayesian Learning: A Diversified Scheme
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Boosted Conformal Prediction Intervals
Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing
Boosting Text-to-Video Generative Model with MLLMs Feedback
Breaking Long-Tailed Learning Bottlenecks: A Controllable Paradigm with Hypernetwork-Generated Diverse Experts
BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO
Bridge-IF: Learning Inverse Protein Folding with Markov Bridges
Calibrating Reasoning in Language Models with Internal Consistency
Can Graph Learning Improve Task Planning?
Can Large Language Model Agents Simulate Human Trust Behavior?
Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs?
Can neural operators always be continuously discretized?
Can Transformers Smell Like Humans?
Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification
CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation
Causal Bandits for Linear Structural Equation Models
Causal Discovery from Event Sequences by Local Cause-Effect Attribution
Causal discovery in the presence of endogenous context variables
Causal-learn: Causal Discovery in Python
Causal Temporal Representation Learning with Nonstationary Sparse Transition
CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition
Certified Adversarial Robustness via Randomized $\alpha$-Smoothing for Regression Models
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model
Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models
CigTime: Corrective Instruction Generation Through Inverse Motion Editing
CLIPCEIL: Boosting Domain Generalization for CLIP by Channel rEfinement and Image-text aLignment
CLIP in Mirror: Disentangling text from visual images through reflection
Cloud Object Detector Adaptation by Integrating Different Source Knowledge
Coarse-to-Fine Concept Bottleneck Models
Codec Avatar Studio: Paired Human Captures for Complete, Driveable, and Generalizable Avatars
CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models
Communication Bounds for the Distributed Experts Problem
Conditional Controllable Image Fusion
Conditioning non-linear and infinite-dimensional diffusion processes
CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting
Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees
Conformal Inverse Optimization
Conjugated Semantic Pool Improves OOD Detection with Pre-trained Vision-Language Models
Consistency Diffusion Bridge Models
Constant Acceleration Flow
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
Continuous Heatmap Regression for Pose Estimation via Implicit Neural Representation
Continuous Product Graph Neural Networks
Contracting with a Learning Agent
CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities
Controlled maximal variability along with reliable performance in recurrent neural networks
ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Ablation Capability for Large Vision-Language Models
CooHOI: Learning Cooperative Human-Object Interaction with Manipulated Object Dynamics
Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification
Cost-aware Bayesian optimization via the Pandora's box Gittins index
CoSW: Conditional Sample Weighting for Smoke Segmentation with Label Noise
CriticEval: Evaluating Large-scale Language Model as Critic
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Cross-video Identity Correlating for Person Re-identification Pre-training
CSPG: Crossing Sparse Proximity Graphs for Approximate Nearest Neighbor Search
Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance
D2R2: Diffusion-based Representation with Random Distance Matching for Tabular Few-shot Learning
DataStealing: Steal Data from Diffusion Models in Federated Learning with Multiple Trojans
D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models
DeBaRA: Denoising-Based 3D Room Arrangement Generation
Decision-Focused Learning with Directional Gradients
DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release
Decoding-Time Language Model Alignment with Multiple Objectives
DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation
DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching
DEL: Discrete Element Learner for Learning 3D Dynamics from 2D Observations
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
Demystify Mamba in Vision: A Linear Attention Perspective
DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging
DePLM: Denoising Protein Language Models for Property Optimization
Derandomizing Multi-Distribution Learning
DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms
DEX: Data Channel Extension for Efficient CNN Inference on Tiny AI Accelerators
DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment
DG-SLAM: Robust Dynamic Gaussian Splatting SLAM with Hybrid Pose Optimization
DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
Differentially Private Optimization with Sparse Gradients
Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features
DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification
DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation
DiffPano: Scalable and Consistent Text to Panorama Generation with Spherical Epipolar-Aware Diffusion
DiffPO: A causal diffusion model for predicting potential outcomes of treatments
DiffuserLite: Towards Real-time Diffusion Planning
Diffusing Differentiable Representations
DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion
DiffusionPDE: Generative PDE-Solving under Partial Observation
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text
Disentangled Style Domain for Implicit $z$-Watermark Towards Copyright Protection
Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation
DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models
Distribution Learning with Valid Outputs Beyond the Worst-Case
Divergences between Language Models and Human Brains
Diversity from the Void: Training Adaptive Agents in Open-Ended Simulators
Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors
Do causal predictors generalize better to new domains?
Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study
DOFEN: Deep Oblivious Forest ENsemble
Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular Videos
Drones Help Drones: A Collaborative Framework for Multi-Drone Object Trajectory Prediction and Beyond
DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks
Dual-Perspective Activation: Efficient Channel Denoising via Joint Forward-Backward Criterion for Artificial Neural Networks
Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models
Dueling over Dessert, Mastering the Art of Repeated Cake Cutting
Dynamical Conditional Optimal Transport through Simulation-Free Flows
Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution
EDT: An Efficient Diffusion Transformer Framework Inspired by Human-like Sketching
Efficiency of the First-Price Auction in the Autobidding World
Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes
Efficient Leverage Score Sampling for Tensor Train Decomposition
Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction
Efficient Sketches for Training Data Attribution and Studying the Loss Landscape
Efficient Temporal Action Segmentation via Boundary-aware Query Voting
EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records
ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer
Elo Uncovered: Robustness and Best Practices in Language Model Evaluation
Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making
Encrypted Data Pruning for Confidential Training of Deep Neural Networks
End-to-end Learnable Clustering for Intent Learning in Recommendation
End-to-End Video Semantic Segmentation in Adverse Weather using Fusion Blocks and Temporal-Spatial Teacher-Student Learning
Enhancing Data Quality via Training Dynamics from Private Domains for Collaborative Fine-Tuning of Large Language Models
Enhancing Large Language Models through Adaptive Tokenizers
Enhancing LLM’s Cognition via Structurization
Enhancing Preference-based Linear Bandits via Human Response Time
Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
Enhancing Zero-Shot Vision Models by Label-Free Prompt Distribution Learning and Bias Correcting
EnOF: Training Accurate Spiking Neural Networks via Enhancing the Output Feature Representation
Entity Alignment with Noisy Annotations from Large Language Models
Entropy testing and its application to testing Bayesian networks
Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention
Evaluating Copyright Takedown Methods for Language Models
Evaluating Numerical Reasoning in Text-to-Image Models
Event-3DGS: Event-based 3D Reconstruction Using 3D Gaussian Splatting
Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation
Exactly Minimax-Optimal Locally Differentially Private Sampling
Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch
Exploiting LLM Quantization
Exploiting Representation Curvature for Boundary Detection in Time Series
Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Following
Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks
Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing
Exploring Prompting Methods for Mitigating Class Imbalance through Synthetic Data Generation with Large Language Models
Expressive Gaussian Human Avatars from Monocular RGB Video
Extending Video Masked Autoencoders to 128 frames
Externally Valid Policy Evaluation from Randomized Trials Using Additional Observational Data
Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems
Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning
Facilitating Multimodal Classification via Dynamically Learning Modality Gap
Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty
FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models
Fairness-Aware Estimation of Graphical Models
Fairness-Aware Meta-Learning via Nash Bargaining
FASTopic: A Fast, Adaptive, Stable, and Transferable Topic Modeling Paradigm
Fearless Stochasticity in Expectation Propagation
Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning
Federated Black-Box Adaptation for Semantic Segmentation
Federated Ensemble-Directed Offline Reinforcement Learning
Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection
FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference
Feint Behaviors and Strategies: Formalization, Implementation and Evaluation
Few-Shot Adversarial Prompt Learning on Vision-Language Models
FIARSE: Model-Heterogeneity Federated Learning via Importance-Aware Submodel Extraction
FindingEmo: An Image Dataset for Emotion Recognition in the Wild
Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models
FineStyle: Fine-grained Controllable Style Personalization for Text-to-image Models
FLAME : Factuality-Aware Alignment for Large Language Models
Flatten Anything: Unsupervised Neural Surface Parameterization
FlexCap: Describe Anything in Images in Controllable Detail
FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation
Focus On What Matters: Separated Models For Visual-Based RL Generalization
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection
Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning
FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention
FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space
Frequency Adaptive Normalization For Non-stationary Time Series Forecasting
From an Image to a Scene: Learning to Imagine the World from a Million 360° Videos
From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization
FUGAL: Feature-fortified Unrestricted Graph Alignment
Fully First-Order Methods for Linearly Constrained Bilevel Optimization
Fully Unconstrained Online Learning
Fundamental Convergence Analysis of Sharpness-Aware Minimization
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion
GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling
GAVEL: Generating Games via Evolution and Language Models
Generalizable and Animatable Gaussian Head Avatar
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming
Generalized Eigenvalue Problems with Generative Priors
Generate Universal Adversarial Perturbations for Few-Shot Learning
Generating Origin-Destination Matrices in Neural Spatial Interaction Models
Generative Modelling of Structurally Constrained Graphs
Genetic-guided GFlowNets for Sample Efficient Molecular Optimization
GENOT: A Neural Optimal Transport Framework for Single Cell Genomics
GenRec: Unifying Video Generation and Recognition with Diffusion Models
Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images
Goal Conditioned Reinforcement Learning for Photo Finishing Tuning
GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes
Gradient Guidance for Diffusion Models: An Optimization Perspective
Gradients of Functions of Large Matrices
Graph Convolutions Enrich the Self-Attention in Transformers!
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization
GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning
HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion
HGDL: Heterogeneous Graph Label Distribution Learning
HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems
How Control Information Influences Multilingual Text Image Generation and Editing?
How does Architecture Influence the Base Capabilities of Pre-trained Language Models? A Case Study Based on FFN-Wider and MoE Transformers
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Human-Assisted Out-of-Distribution Generalization and Detection
HyperDDPM: Estimating Epistemic and Aleatoric Uncertainty with a Single Model
I Bet You Did Not Mean That: Semantic Importance of Any Classifier via Betting
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data
Identifying spatio-temporal relations between anomalies and extreme events
II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos
Image Textualization: An Automatic Framework for Generating Rich and Detailed Image Descriptions
IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design Patents
Implicit Bias of Mirror Flow on Separable Data
Implicit Multimodal Alignment: On the Generalization of Frozen LLMs to Multimodal Inputs
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations
Improved Regret of Linear Ensemble Sampling
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
Improving Equivariant Model Training via Constraint Relaxation
Improving Generalization and Convergence by Enhancing Implicit Regularization
Improving Logits-based Detector without Logits from Black-box LLMs
Improving Neural Network Surface Processing with Principal Curvatures
Improving Neural ODE Training with Temporal Adaptive Batch Normalization
INDICT: Code Generation with Internal Dialogues of Critiques for Both Security and Helpfulness
Induced Model Matching: Restricted Models Help Train Full-Featured Models
Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference
Initializing Services in Interactive ML Systems for Diverse Users
In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment
Integrating GNN and Neural ODEs for Estimating Two-Body Interactions in Mixed-Species Collective Motion
InterDreamer: Less Supervision for More Generalizable Text-Driven 3D Human-Object Interaction Synthesis
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Interpretable Concept-Based Memory Reasoning
Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents
Intervention and Conditioning in Causal Bayesian Networks
IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors
Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions
Is Cross-validation the Gold Standard to Evaluate Model Performance?
Is Knowledge Power? Dissecting Information Asymmetry In Repeated Games
Is Your LiDAR Placement Optimized for 3D Scene Understanding?
Iteration Head: A Mechanistic Study of Chain-of-Thought
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
Kernel PCA for Out-of-Distribution Detection
KFNN: K-Free Nearest Neighbor For Crowdsourcing
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
Large Language Models Play StarCraft II:Benchmarks and A Chain of Summarization Approach
Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning
Latent Intrinsics Emerge from Training to Relight
Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks
Layer-Adaptive $\mathcal{H}_\infty$ State Pruning for Deep Diagonal State Space Model Compression
Learn Incrementally from An Ongoing Trajectory: A Provable In-Trajectory Inverse Reinforcement Learning Framework
Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training
Learning-Augmented Algorithms for the Bahncard Problem
Learning-Augmented Algorithms with Explicit Predictors
Learning-Augmented Approximation Algorithms for Maximization Problems
Learning Conjunctive Representations
Learning from Noisy Labels via Conditional Distributionally Robust Optimization
Learning Macroscopic Dynamics from Partial Microscopic Observations
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
Learning Partitions from Context
Learning Structure-Aware Representations of Dependent Types
Learning Structured Representations with Hyperbolic Embeddings
Learning the Latent Causal Structure for Modeling Label Noise
Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games
Learning to Cooperate with Humans using Generative Agents
Learning to Edit Visual Programs with Self-Supervision
Learning to Embed Distributions via Maximum Kernel Entropy
Learning to Reason via Program Generation, Emulation, and Search
Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way
Lever LM: Configuring In-Context Sequence to Lever Large Vision Language Models
Lexicon3D: Probing Visual Encoding Models for Complex 3D Scene Understanding
LiveScene: Language Embedding Interactive Radiance Fields for Physical Scene Control and Rendering
LLaMo: Large Language Model-based Molecular Graph Assistant
LLM Dataset Inference: Detect Datasets, not Strings
LLMDFA: Analyzing Dataflow in Code with Large Language Models
LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language
Localized Adaptive Risk Control
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
LoCo: Learning 3D Location-Consistent Image Features with a Memory-Efficient Ranking Loss
LoD-Loc: Aerial Visual Localization using LoD 3D Map with Neural Wireframe Alignment
LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding
LoRA-GA: Low-Rank Adaptation with Gradient Approximation
Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization
Low Precision Local Training is Enough for Federated Learning
LT-Defense: Searching-free Backdoor Defense via Exploiting Long-Tailed Effect
Make the Most of Your Data: Changing the Training Data Distribution to Improve Generalization
MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space
Marginalized Hamiltonian Monte Carlo for Linear Mixed-Effects Models
Marrying Causal Representation Learning with Dynamical Systems for Science
Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages
MaskFactory: Towards High-quality Synthetic Data Generation For Dichotomous Image Segmentation
Matching the Statistical Query Lower Bound for $k$-Sparse Parity Problems with Stochastic Gradient Descent
MatFormer: Nested Transformer for Elastic Inference
Maximizing utility in multi-agent environments by anticipating the behavior of other learners
Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models
Mechanism design augmented with output advice
Membership Inference Attacks against Large Vision-Language Models
MeshXL: Neural Coordinate Field for Generative 3D Foundation Models
MetaCURL: Non-stationary Concave Utility Reinforcement Learning
Metric Transforms and Low Rank Representations of Kernels
MG-Net: Automatically Customize QAOA with Quantum Hardware Constraints for Enhanced Performance
MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs
MILP-StuDio: MILP Instance Generation via Block Structure Decomposition
Mind the Gap Between Prototypes and Images in Cross-domain Few-shot Classification
MiniCache: KV Cache Compression in Depth Dimension for Large Language Models
Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning
Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization
Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor
Mixture of Nested Experts: Adaptive Processing of Visual Tokens
Mixture of Scales: Memory-Efficient Token-Adaptive Binarization for Large Language Models
MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models
MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding
MMLONGBENCH-DOC: Benchmarking Long-context Document Understanding with Visualizations
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark
Model Collapse Demystified: The Case of Regression
Model Fusion through Bayesian Optimization in Language Model Fine-Tuning
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems
Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory
Model Sensitivity Aware Continual Learning
MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks
Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation
Mr.Bean: A Comprehensive Meta-Reasoning Benchmark for Analyzing Large Language Models
MSA Generation with Seqs2Seqs Pretraining: Advancing Protein Structure Predictions
Multidimensional Fractional Programming for Normalized Cuts
Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded Images
Multimodal Large Language Models Make Text-to-Image Generative Models Align Better
MultiPull: Detailing Signed Distance Functions by Pulling Multi-Level Queries at Multi-Step
Multi-Reward Best Policy Identification
Multi-Scale Representation Learning for Protein Fitness Prediction
Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model
Multi-times Monte Carlo Rendering for Inter-reflection Reconstruction
Multi-turn Reinforcement Learning with Preference Human Feedback
Multi-view Masked Contrastive Representation Learning for Endoscopic Video Analysis
Natural Counterfactuals With Necessary Backtracking
NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
Nearly Tight Black-Box Auditing of Differentially Private Machine Learning
Near-Optimal Approximation of Matrix Functions by the Lanczos Method
Near-Optimality of Contrastive Divergence Algorithms
Nesterov acceleration despite very noisy gradients
Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times
Neural Isometries: Taming Transformations for Equivariant ML
Neural Network Reparametrization for Accelerated Optimization in Molecular Simulations
NN4SysBench: Characterizing Neural Network Verification for Computer Systems
No Free Lunch in LLM Watermarking: Trade-offs in Watermarking Design Choices
No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation
NoiseGPT: Label Noise Detection and Rectification through Probability Curvature
Noisy Ostracods: A Fine-Grained, Imbalanced Real-World Dataset for Benchmarking Robust Machine Learning and Label Correction Methods
Non-asymptotic Convergence of Training Transformers for Next-token Prediction
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks
Normalization and effective learning rates in reinforcement learning
Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in Transformers
Norms for Managing Datasets: A Systematic Review of NeurIPS Datasets
NovoBench: Benchmarking Deep Learning-based \emph{De Novo} Sequencing Methods in Proteomics
Nuclear Fusion Diamond Polishing Dataset
OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step
Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality
Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff
Off-policy estimation with adaptively collected data: the power of online learning
Off-Policy Selection for Initiating Human-Centric Experimental Design
OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI
One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently
One-Step Effective Diffusion Network for Real-World Image Super-Resolution
On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models
Online Budgeted Matching with General Bids
Online Composite Optimization Between Stochastic and Adversarial Environments
Online Control with Adversarial Disturbance for Continuous-time Linear Systems
Online Estimation via Offline Estimation: An Information-Theoretic Framework
Online Non-convex Learning in Dynamic Environments
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models
On scalable oversight with weak LLMs judging strong LLMs
On Softmax Direct Preference Optimization for Recommendation
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
On the Computational Landscape of Replicable Learning
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
On the Implicit Bias of Predicting in Latent Space in Self Supervised Learning
On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games
On the Stability and Generalization of Meta-Learning
On the Use of Anchoring for Training Vision Models
On Weak Regret Analysis for Dueling Bandits
OpenGaussian: Towards Point-Level 3D Gaussian-based Open Vocabulary Understanding
Optimal Design for Human Feedback
Oracle-Efficient Differentially Private Learning with Public Data
Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling
Ordering-Based Causal Discovery for Linear and Nonlinear Relations
OW-VISCapTor: Abstractors for Open-World Video Instance Segmentation and Captioning
P$^2$C$^2$Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics
PaCE: Parsimonious Concept Engineering for Large Language Models
Parallel Backpropagation for Shared-Feature Visualization
Parallelizing Model-based Reinforcement Learning Over the Sequence Length
Parameter-Inverted Image Pyramid Networks
Parameterized Approximation Schemes for Fair-Range Clustering
PCoTTA: Continual Test-Time Adaptation for Multi-Task Point Cloud Understanding
Pearls from Pebbles: Improved Confidence Functions for Auto-labeling
Personalized Federated Learning via Feature Distribution Adaptation
PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting
Physics-Constrained Comprehensive Optical Neural Networks
Piecewise-Stationary Bandits with Knapsacks
Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-shot Molecular Property Prediction
Policy Aggregation
Policy Mirror Descent with Lookahead
Polynomial-Time Computation of Exact $\Phi$-Equilibria in Polyhedral Games
Posture-Informed Muscular Force Learning for Robust Hand Pressure Estimation
PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond
Precise Relational DNN Verification With Cross Executional Branching
Predicting the Performance of Foundation Models via Agreement-on-the-Line
Prediction-Powered Ranking of Large Language Models
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors
Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training
Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics
Probabilistic Graph Rewiring via Virtual Nodes
Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach
Procedure-Aware Surgical Video-language Pretraining with Hierarchical Knowledge Augmentation
ProG: A Graph Prompt Learning Benchmark
Progressive Entropic Optimal Transport Solvers
Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning
Proportional Fairness in Non-Centroid Clustering
ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention
ProtGO: Function-Guided Protein Modeling for Unified Representation Learning
Provable Benefit of Cutout and CutMix for Feature Learning
Provable Tempered Overfitting of Minimal Nets and Typical Nets
Provably Efficient Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs
ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Process
Proximal Causal Inference With Text Data
Putting Gale & Shapley to Work: Guaranteeing Stability Through Learning
PUZZLES: A Benchmark for Neural Algorithmic Reasoning
QT-ViT: Improving Linear Attention in ViT with Quadratic Taylor Expansion
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation
QueST: Self-Supervised Skill Abstractions for Learning Continuous Control
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation
Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding
RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier
Rapid Plug-in Defenders
Reactzyme: A Benchmark for Enzyme-Reaction Prediction
RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models
Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
RealMAN: A Real-Recorded and Annotated Microphone Array Dataset for Dynamic Speech Enhancement and Localization
REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR
Reconstruction of Manipulated Garment with Guided Deformation Prior
Reimagining Mutual Information for Enhanced Defense against Data Leakage in Collaborative Inference
Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer
Relationship Prompt Learning is Enough for Open-Vocabulary Semantic Segmentation
Renovating Names in Open-Vocabulary Segmentation Benchmarks
[Re] On the Reproducibility of Post-Hoc Concept Bottleneck Models
ReplaceAnything3D: Text-Guided Object Replacement in 3D Scenes with Compositional Scene Representations
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content
Reproducibility of predictive networks for mouse visual cortex
Reproducibility study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"
Reproducibility Study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"
ResAD: A Simple Framework for Class Generalizable Anomaly Detection
Rethinking Fourier Transform for Long-term Time Series Forecasting: A Basis Functions Perspective
Rethinking Imbalance in Image Super-Resolution for Efficient Inference
Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity
Rethinking No-reference Image Exposure Assessment from Holism to Pixel: Models, Datasets and Benchmarks
Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation
Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models
Revisiting Ensembling in One-Shot Federated Learning
Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
Reward Learning from Human Demonstration Improves Supervised Fine-tuning for LLM Alignment
Reward Machines for Deep RL in Noisy and Uncertain Environments
RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation
Risk-Averse Finetuning of Large Language Models
RL-GPT: Integrating Reinforcement Learning and Code-as-policy
Robust Graph Neural Networks via Unbiased Aggregation
Robustly overfitting latents for flexible neural image compression
Robust Mixture Learning when Outliers Overwhelm Small Groups
Robust Neural Contextual Bandit against Adversarial Corruptions
RoleAgent: Building, Interacting, and Benchmarking High-quality Role-Playing Agents from Scripts
Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
Saliency-driven Experience Replay for Continual Learning
Sample Complexity of Posted Pricing for a Single Item
Sample Efficient Bayesian Learning of Causal Graphs from Interventions
Sample-Efficient Private Learning of Mixtures of Gaussians
Sample-efficient Simulation-based Inference for Urban Travel Demand Calibration
SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series
SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain
Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation
Schur Nets: exploiting local structure for equivariance in higher order graph neural networks
Score-based 3D molecule generation with neural fields
Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets
SCube: Instant Large-Scale Scene Reconstruction using VoxSplats
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training
SEA: State-Exchange Attention for High-Fidelity Physics-Based Transformers
SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling
SEEV: Synthesis with Efficient Exact Verification for ReLU Neural Barrier Functions
Segment Anything without Supervision
Segment, Shuffle, and Stitch: A Simple Mechanism for Improving Time-Series Representations
Selective Generation for Language Models
Self-Labeling the Job Shop Scheduling Problem
Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation
Self-playing Adversarial Language Game Enhances LLM Reasoning
Self-supervised Transformation Learning for Equivariant Representations
Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models
Semantic and Spatial Adaptive Pixel-level Classifier for Semantic Segmentation
Semantic Density: Uncertainty Quantification in Semantic Space for Large Language Models
Semantic Routing via Autoregressive Modeling
SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified Flow
Semidefinite Relaxations of the Gromov-Wasserstein Distance
Semi-Open 3D Object Retrieval via Hypergraph-Based Hierarchical Equilibrium Representation
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics
Separations in the Representational Capabilities of Transformers and Recurrent Architectures
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation
SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation
Set-Based Prompting: Provably Solving the Language Model Order Dependency Problem
shapiq: Shapley Interactions for Machine Learning
SILENCE: Protecting privacy in offloaded speech understanding on wimpy devices
SkipPredict: When to Invest in Predictions for Scheduling
SLICE-100K: A Multimodal Dataset for Extrusion-based 3D Printing
SlimGPT: Layer-wise Structured Pruning for Large Language Models
SlimSAM: 0.1% Data Makes Segment Anything Slim
Small coresets via negative dependence: DPPs, linear statistics, and concentration
SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction
S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search
SocraticLM: Exploring Socratic Personalized Teaching with Large Language Models
Soft Tensor Product Representations for Fully Continuous, Compositional Visual Representations
Solving Sparse \& High-Dimensional-Output Regression via Compression
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries
SpeAr: A Spectral Approach for Zero-Shot Node Classification
Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration
Speculative Monte-Carlo Tree Search
SpelsNet: Surface Primitive Elements Segmentation by B-Rep Graph Structure Supervision
Spiking Transformer with Experts Mixture
Splatter a Video: Video Gaussian Representation for Versatile Processing
SplitNeRF: Split Sum Approximation Neural Field for Joint Geometry, Illumination, and Material Estimation
SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation
SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image Super-Resolution
SS3DM: Benchmarking Street-View Surface Reconstruction with a Synthetic 3D Mesh Dataset
ST$_k$: A Scalable Module for Solving Top-k problems
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes
Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation
Statistical Efficiency of Distributional Temporal Difference
Stochastic Optimal Control Matching
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data
Stopping Bayesian Optimization with Probabilistic Regret Bounds
StreamBench: Towards Benchmarking Continuous Improvement of Language Agents
StreamFlow: Streamlined Multi-Frame Optical Flow Estimation for Video Sequences
Streaming Long Video Understanding with Large Language Models
Structural Inference of Dynamical Systems with Conjoined State Space Models
Structured flexibility in recurrent neural networks via neuromodulation
SubjECTive-QA: A dataset for the subjective evaluation of answers in Earnings Call Transcripts (ECTs)
Subsurface Scattering for Gaussian Splatting
Suitable is the Best: Task-oriented Knowledge Fusion in Vulnerability Detection
Super Consistency of Neural Network Landscapes and Learning Rate Transfer
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
Symmetries In-Context: Universal Self-Supervised Learning through Contextual World Models
Symmetry Discovery Beyond Affine Transformations
TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy
Taming the Long Tail in Human Mobility Prediction
Task Me Anything
Temporally Consistent Atmospheric Turbulence Mitigation with Neural Representations
Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
The AlCHEmist: Automated Labeling 500x CHEaper than LLM Data Annotators
The Challenges of the Nonlinear Regime for Physics-Informed Neural Netowrks
The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
The Impact of Initialization on the Finetuning Dynamics in LoRA
The Implicit Bias of Gradient Descent on Separable Multiclass Data
The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels
The motion planning neural circuit in goal-directed navigation as Lie group operator search
The Multimodal Universe: Enabling Large-Scale Machine Learning with 70TBs of Astronomical Scientific Data
The Sample-Communication Complexity Trade-off in Federated Q-Learning
The Selective $G$-Bispectrum and its Inversion: Applications to $G$-Invariant Networks
Through the Looking-Glass: Tracing Shifts in AI Data Consent across the Web
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
TopoLogic: An Interpretable Pipeline for Lane Topology Reasoning on Driving Scenes
Toward Efficient Inference for Mixtures of Experts
Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics
Towards a theory of how the structure of language is acquired by deep neural networks
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
Towards Fast Exact Conformalization of Generalized Parametric Estimation
Towards Global Optimal Visual In-Context Learning Prompt Selection
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
Towards More Efficient Property Inference Attacks on Graph Neural Networks
Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking
Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels
Towards Robust Multimodal Sentiment Analysis with Incomplete Data
Towards Safe Concept Transfer of Multi-Modal Diffusion via Causal Representation Editing
Towards Universal Mesh Movement Networks
Training an Open-Vocabulary Monocular 3D Detection Model without 3D Data
Training Data Attribution via Approximate Unrolling
TrajCLIP: Pedestrian trajectory prediction method using contrastive learning and idempotent networks
Transferring disentangled representations: bridging the gap between synthetic and real images
Transformers Represent Belief State Geometry in their Residual Stream
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models
Truthful High Dimensional Sparse Linear Regression
Two-way Deconfounder for Off-policy Evaluation under Unmeasured Confounding
Typicalness-Aware Learning for Failure Detection
UDKAG: Augmenting Large Vision-Language Models with Up-to-Date Knowledge
Uncertainty-aware Fine-tuning of Segmentation Foundation Models
Uncovering Safety Risks of Large Language Models through Concept Activation Vector
Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation
Understanding Hallucinations in Diffusion Models through Mode Interpolation
Understanding, Rehearsing, and Introspecting: Learn a Policy from Textual Tutorial Books in Football Games
Understanding the expressivity and trainability of Fourier Neural Operator
Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem
Unified Generative and Discriminative Training for Multi-modal Large Language Models
Unified Insights: Harnessing Multi-modal Data for Phenotype Imputation via View Decoupling
UniGAD: Unifying Multi-level Graph Anomaly Detection
UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems
Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation
Unlocking the Potential of Global Human Expertise
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models
Unraveling the Gradient Descent Dynamics of Transformers
Unsupervised Modality Adaptation with Text-to-Image Diffusion Models for Semantic Segmentation
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
Unveiling The Matthew Effect Across Channels: Assessing Layer Width Sufficiency via Weight Norm Variance
Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series
Variational Distillation of Diffusion Policies into Mixture of Experts
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
VastTrack: Vast Category Visual Object Tracking
VCR-GauS: View Consistent Depth-Normal Regularizer for Gaussian Surface Reconstruction
Video Diffusion Models are Training-free Motion Interpreter and Controller
VideoTetris: Towards Compositional Text-to-Video Generation
VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks
Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability
Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
Visual Riddles: a Commonsense and World Knowledge Challenge for Large Vision and Language Models
Vitron: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing
VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance
Wasserstein Gradient Boosting: A General Framework with Applications to Posterior Regression
WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off
Weakly Supervised Referring Image Segmentation via Progressive Comprehension
WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
What Factors Affect Multi-modal In-Context Learning? An In-Depth Exploration
What Makes Partial-Label Learning Algorithms Effective?
What Makes Safety Fine-tuning Methods Safe? A Mechanistic Study
WildGaussians: 3D Gaussian Splatting In the Wild
WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
You Don't Need Data-Augmentations in Self-Supervised Learning
Your contrastive learning problem is secretly a distribution alignment problem
Zero-Shot Event-Intensity Asymmetric Stereo via Visual Prompting from Image Domain
Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection
(ends 7:30 PM)
Creative AI Session 4 [4:30-4:33]
(ends 4:33 PM)
Break:
Coffee Break
(ends 5:30 PM)

THU 12 DEC
7:30 a.m.
Registration (East & West)
(ends 6:00 PM)
Break:
Coffee Break
(ends 8:30 AM)
8:30 a.m.
Invited Talk:
Invited Talk - Lidong Zhou
Lidong Zhou
(ends 9:30 AM)
9:30 a.m.
Break:
Coffee Break
(ends 10:00 AM)
10 a.m.
Oral Session 3A [10:00-11:00]
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
Return of Unconditional Generation: A Self-supervised Representation Generation Method
HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
(ends 11:00 AM)
Oral Session 3B [10:00-11:00]
Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions
Solving Intricate Problems with Human-like Decomposition and Rethinking
Questioning the Survey Responses of Large Language Models
(ends 11:00 AM)
Oral Session 3C [10:00-11:00]
PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression
LLM Evaluators Recognize and Favor Their Own Generations
Unlocking the Boundaries of Thought: A Reasoning Granularity Framework to Quantify and Optimize Chain-of-Thought
(ends 11:00 AM)
Oral Session 3D [10:00-11:00]
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs
Not All Tokens Are What You Need for Pretraining
(ends 11:00 AM)
11 a.m.
Poster Session 3 [11:00-2:00]
Posters 11:00-2:00
1-bit quanta video reconstruction via self-supervised photon prediction
AGILE: A Novel Framework of LLM Agent
A Synthetic Dataset for Personal Attribute Inference
Bilevel Optimization with Lower-Level Contextual MDPs
CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes
Constrained Synthesis with Projected Diffusion Models
Dimension-free deterministic equivalents for random feature regression
Efficient Policy Evaluation Across Multiple Different Experimental Datasets
Generative Forests
Generative Semi-supervised Graph Anomaly Detection
Learning Low-Rank Feature for Thorax Disease Classification
Learning on Large Graphs using Intersecting Communities
Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments
MO-DDN: A Coarse-to-Fine Attribute-based Exploration Agent for Multi-Object Demand-driven Navigation
Neural Concept Binder
Optimal Multi-Fidelity Best-Arm Identification
Quantum Deep Equilibrium Models
Recursive Introspection: Teaching Foundation Model Agents How to Self-Improve
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts
Statistical Inference for Fairness Auditing
Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
Tolerant Algorithms for Learning with Arbitrary Covariate Shift
Towards Dynamic Message Passing on Graphs
Trade-Offs of Diagonal Fisher Information Matrix Estimators
Why the Metric Backbone Preserves Community Structure
Yo'LLaVA: Your Personalized Language and Vision Assistant
Zero-to-Hero: Enhancing Zero-Shot Novel View Synthesis via Attention Map Filtering
$\textit{Bifr\"ost}$: 3D-Aware Image Composing with Language Instructions
$\textit{NeuroPath}$: A Neural Pathway Transformer for Joining the Dots of Human Connectomes
$\texttt{ConflictBank}$: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLMs
$\texttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning
3D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization
Abductive Reasoning in Logical Credal Networks
A Benchmark Dataset for Event-Guided Human Pose Estimation and Tracking in Extreme Conditions
A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types
Accelerating Matroid Optimization through Fast Imprecise Oracles
Accelerating Nash Equilibrium Convergence in Monte Carlo Settings Through Counterfactual Value Based Fictitious Play
Accelerating Relative Entropy Coding with Space Partitioning
Achieving Constant Regret in Linear Markov Decision Processes
Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes
A Closer Look at the CLS Token for Cross-Domain Few-Shot Learning
Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting
AdanCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer
Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis
Adaptive Depth Networks with Skippable Sub-Paths
AdjointDEIS: Efficient Gradients for Diffusion Models
Advancing Cross-domain Discriminability in Continual Learning of Vison-Language Models
Adversarially Robust Multi-task Representation Learning
Adversarial Schrödinger Bridge Matching
AED: Adaptable Error Detection for Few-shot Imitation Policy
AFBench: A Large-scale Benchmark for Airfoil Design
A Foundation Model for Zero-shot Logical Query Reasoning
Agent Planning with World Knowledge Model
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data
Alias-Free Mamba Neural Operator
Aligning Large Language Models with Representation Editing: A Control Perspective
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization
AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queries
Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object Detection
A Modular Conditional Diffusion Framework for Image Reconstruction
AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback
Analysing the Generalisation and Reliability of Steering Vectors
Analytically Computing Partial Information Decomposition
Analytic Nonlinear Dynamical System Identification with Non-asymptotic Guarantees
An Analysis of Elo Rating Systems via Markov Chains
An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning
An Any-to-Any Vision Model for Tens of Tasks and Modalities
An Autoencoder-Like Nonnegative Matrix Co-Factorization for Improved Student Cognitive Modeling
An effective framework for estimating individualized treatment rule with multi-category treatments
A Neural Network Approach for Efficiently Answering Most Probable Explanation Queries in Probabilistic Models
Animate3D: Animating Any 3D Model with Multi-view Video Diffusion
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing
A Non-parametric Direct Learning Approach to Heterogeneous Treatment Effect Estimation under Unmeasured Confounding
Apathetic or Empathetic? Evaluating LLMs' Emotional Alignments with Humans
APEBench: A Benchmark for Autoregressive Neural Emulators of PDEs
APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets
Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models
Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering
Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era
Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields
ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users
Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis
A Simple Image Segmentation Framework via In-Context Examples
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective
Assemblage: Automatic Binary Dataset Construction for Machine Learning
A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm
A theoretical design of concept sets: improving the predictability of Concept Bottleneck Models
A Tractable Inference Perspective of Offline RL
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
A Unified Framework for 3D Scene Understanding
AutoManual: Generating Instruction Manuals by LLM Agents via Interactive Environmental Learning
Autonomous Driving with Spiking Neural Networks
Autoregressive Image Generation without Vector Quantization
AvaTaR: Optimizing LLM Agents for Tool-Assisted Knowledge Retrieval
B$\oplus$LD: Boolean Logic Deep Learning
Back to the Continuous Attractors
Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs
BAKU: An Efficient Transformer for Multi-Task Policy Learning
BAN: Detecting Backdoors Activated by Neuron Noise
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable
Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks
Benign overfitting in leaky ReLU networks with moderate input dimension
BERTs are Generative In-Context Learners
BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation
Beyond Assouad, Fano, and Le Cam: Toward Unified Lower Bounds for Statistical Estimation and Interactive Decision Making
Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints
Beyond task diversity: provable representation transfer for sequential multitask linear bandits
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training
Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature
Binary Search Tree with Distributional Predictions
Biomedical Visual Instruction Tuning with Clinician Preference Alignment
BiScope: AI-generated Text Detection by Checking Memorization of Preceding Tokens
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
Boosting Graph Pooling with Persistent Homology
Boosting the Potential of Large Language Models with an Intelligent Information Assistant
Boundary Decomposition for Nadir Objective Vector Estimation
Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views
Bridging Geometric States via Generative Modeling
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
Calibrated Preference Optimization for Direct Language Model Alignment
Can Language Models Learn to Skip Steps?
Can Large Language Models Analyze Graphs like Professionals? A Benchmark and Dataset
Can Learned Optimization Make Reinforcement Learning Less Difficult?
Can Models Learn Skill Composition from Examples?
Cardinality-Aware Set Prediction and Top-$k$ Classification
Cascade Speculative Drafting for Even Faster LLM Inference
Causal Context Adjustment Loss for Learned Image Compression
Causal Contrastive Learning for Counterfactual Regression Over Time
Causal Deciphering and Inpainting in Spatio-Temporal Dynamics via Diffusion Model
Causal Dependence Plots
Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects
Causal language modeling can elicit search and reasoning capabilities on sudoku puzzles
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
ChatCam: Empowering Camera Control through Conversational AI
ChatQA: Surpassing GPT-4 on Conversational QA and RAG
Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models
ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions
Class-wise Transformation Is All You Need
CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses
Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention
CogVLM: Visual Expert for Pretrained Language Models
Collaborative Cognitive Diagnosis with Disentangled Representation Learning
Color-Oriented Redundancy Reduction in Dataset Distillation
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching
Communication-Efficient Federated Group Distributionally Robust Optimization
Community Detection Guarantees using Embeddings Learned by Node2Vec
Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference
Compressing Large Language Models using Low Rank and Low Precision Decomposition
Compressive Sensing with Sparsity Inducing Conditionally Gaussian Generative Models
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
Computation Tree: A Transferable Pattern Towards Graph Foundation Models
Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand
Confident Natural Policy Gradient for Local Planning in $q_\pi$-realizable Constrained MDPs
Conformalized Multiple Testing after Data-dependent Selection
Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
Confusion-Resistant Federated Learning via Diffusion-Based Data Harmonization on Non-IID Data
Constrained Human-AI Cooperation: An Inclusive Embodied Social Intelligence Challenge
Continual Counting with Gradual Privacy Expiration
Continual Learning with Global Alignment
Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT
Controlling Continuous Relaxation for Combinatorial Optimization
Convergence Analysis of Split Federated Learning on Heterogeneous Data
Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods
CorDA: Context-Oriented Decomposition Adaptation of Large Language Models
Cost-efficient Knowledge-based Question Answering with Large Language Models
CoSy: Evaluating Textual Explanations of Neurons
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
Covariate Shift Corrected Conditional Randomization Test
cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers
Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions
Crafting Interpretable Embeddings by Asking LLMs Questions
Croissant: A Metadata Format for ML-Ready Datasets
Cross-Modality Perturbation Synergy Attack for Person Re-identification
Cross-model Control: Improving Multiple Large Language Models in One-time Training
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for Bird's Eye View Object Detection
Cryptographic Hardness of Score Estimation
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation
CV-VAE: A Compatible Video VAE for Latent Generative Video Models
DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation
Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning
Data curation via joint example selection further accelerates multimodal learning
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning
DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain
DDK: Distilling Domain Knowledge for Efficient Large Language Models
DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting
Decentralized Noncooperative Games with Coupled Decision-Dependent Distributions
Deep Equilibrium Algorithmic Reasoning
Deep Learning in Medical Image Registration: Magic or Mirage?
DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised $h$-transform
Delving into the Reversal Curse: How Far Can Large Language Models Generalize?
Demystifying Encoding: Detecting Explanations that Hide Information in the Selection
DeNetDM: Debiasing by Network Depth Modulation
Detecting Bugs with Substantial Monetary Consequences by LLM and Rule-based Reasoning
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
DiChaViT: Diverse Representations Boosts Channel-Adaptive Vision Transformers
DiffSF: Diffusion Models for Scene Flow Estimation
Diffusion4D: Fast Spatial-temporal Consistent 4D generation via Video Diffusion Models
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion
Diffusion Imitation from Observation
Diffusion-Inspired Truncated Sampler for Text-Video Retrieval
Diffusion Models are Certifiably Robust Classifiers
DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection
Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer
Discovering Creative Behaviours through DUPLEX: Diverse Universal Features for Policy Exploration
Discovering Preference Optimization Algorithms with and for Large Language Models
Discrete Dictionary-based Decomposition Layer for Structured Representation Learning
Discrete-state Continuous-time Diffusion for Graph Generation
Disentangling and mitigating the impact of task similarity for continual learning
Dissecting the Failure of Invariant Learning on Graphs
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features
Distributed-Order Fractional Graph Operating Network
Distributed Sparse Regression via Penalization
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup
DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection
DreamCatcher: A Wearer-aware Multi-modal Sleep Event Dataset Based on Earables in Non-restrictive Environments
DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion Models
DRIP: Unleashing Diffusion Priors for Joint Foreground and Alpha Prediction in Image Matting
Dual-Diffusion for Binocular 3D Human Pose Estimation
Dual Lagrangian Learning for Conic Optimization
DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs
Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
e-COP : Episodic Constrained Optimization of Policies
Edit Distance Robust Watermarks via Indexing Pseudorandom Codes
EEGPT: Pretrained Transformer for Universal and Reliable Representation of EEG Signals
EEVR: A Virtual Reality-Based Emotion Dataset Featuring Paired Physiological Signals and Textual Descriptions
Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games
Efficient Adversarial Training in LLMs with Continuous Attacks
Efficient and Private Marginal Reconstruction with Local Non-Negativity
Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing
Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance
Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rate
Elucidating the Design Space of Dataset Condensation
End-To-End Causal Effect Estimation from Unstructured Text Data
End-to-End Ontology Learning with Large Language Models
Energy-based Epistemic Uncertainty for Graph Neural Networks
Energy-based Hopfield Boosting for Out-of-Distribution Detection
Enhancing Chess Reinforcement Learning with Graph Representation
Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective
Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control
Ensemble Learning for Heterogeneous Large Language Models with Deep Parallel Collaboration
EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture Models
Entrywise error bounds for low-rank approximations of kernel matrices
Epipolar-Free 3D Gaussian Splatting for Generalizable Novel View Synthesis
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters
Equivariant Neural Diffusion for Molecule Generation
Error Analysis of Spherically Constrained Least Squares Reformulation in Solving the Stackelberg Prediction Game
Error Correction Output Codes for Robust Neural Networks against Weight-errors: A Neural Tangent Kernel Point of View
Even Sparser Graph Transformers
Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals
Exocentric-to-Egocentric Video Generation
Expert-level protocol translation for self-driving labs
Explaining RL Decisions with Trajectories': A Reproducibility Study
Explaining Text Datasets with Language Parameters
Exploring Adversarial Robustness of Deep State Space Models
Exploring Molecular Pretraining Model at Scale
Exponential Quantum Communication Advantage in Distributed Inference and Learning
Extending Multi-modal Contrastive Representations
Extensive-Form Game Solving via Blackwell Approachability on Treeplexes
Face2QR: A Unified Framework for Aesthetic, Face-Preserving, and Scannable QR Code Generation
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding?
Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation
Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior
FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings
Fast and Memory-Efficient Video Diffusion Using Streamlined Inference
Fast Channel Simulation via Error-Correcting Codes
Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
Fast Rates for Bandit PAC Multiclass Classification
Fast samplers for Inverse Problems in Iterative Refinement models
Fast yet Safe: Early-Exiting with Risk Control
Feature-Level Adversarial Attacks and Ranking Disruption for Visible-Infrared Person Re-identification
FedGMark: Certifiably Robust Watermarking for Federated Graph Learning
FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning
Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark
FewViewGS: Gaussian Splatting with Few View Matching and Multi-stage Training
FFAM: Feature Factorization Activation Map for Explanation of 3D Detectors
FIDE: Frequency-Inflated Conditional Diffusion Model for Extreme-Aware Time Series Generation
Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random
Fine-grained Image-to-LiDAR Contrastive Distillation with Visual Foundation Models
First-Order Minimax Bilevel Optimization
Fit for our purpose, not yours: Benchmark for a low-resource, Indigenous language
FiVA: Fine-grained Visual Attribute Dataset for Text-to-Image Diffusion Models
Foundations of Multivariate Distributional Reinforcement Learning
Frequency-aware Generative Models for Multivariate Time-series Imputation
FRIEREN: Efficient Video-to-Audio Generation with Rectified Flow Matching
From Causal to Concept-Based Representation Learning
From Instance Training to Instruction Learning: Task Adapters Generation from Instructions
Functional Bilevel Optimization for Machine Learning
FUNGI: Features From Unsupervised Gradients
GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting
Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images
GaussianMarker: Uncertainty-Aware Copyright Protection of 3D Gaussian Splatting
Gaussian Process Bandits for Top-k Recommendations
Generalization Bounds via Conditional $f$-Information
Generalized Protein Pocket Generation with Prior-Informed Flow Matching
GeoLife: Spacial Plant Species Prediction Dataset
GeoLRM: Geometry-Aware Large Reconstruction Model for High-Quality 3D Gaussian Generation
Geometric-Averaged Preference Optimization for Soft Preference Labels
Geometric Exploitation for Indoor Panoramic Semantic Segmentation
Geometric Trajectory Diffusion Models
Geometry Awakening: Cross-Geometry Learning Exhibits Superiority over Individual Structures
GO4Align: Group Optimization for Multi-Task Alignment
Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization
Gradient Methods for Online DR-Submodular Maximization with Stochastic Long Term Constraints
Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization
GRANOLA: Adaptive Normalization for Graph Neural Networks
Graph-based Uncertainty Metrics for Long-form Language Model Generations
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models
Graph Coarsening with Message-Passing Guarantees
Graph Diffusion Policy Optimization
Graph neural networks and non-commuting operators
GUIDE: Real-Time Human-Shaped Agents
Hamba: Single-view 3D Hand Reconstruction with Graph-guided Bi-Scanning Mamba
Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient
Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
Harmonizing Visual Text Comprehension and Generation
Harmony4D: A Video Dataset for In-The-Wild Close Human Interactions
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
HiCo: Hierarchical Controllable Diffusion Model for Layout-to-image Generation
HiCoM: Hierarchical Coherent Motion for Dynamic Streamable Scenes with 3D Gaussian Splatting
Hierarchical and Density-based Causal Clustering
Hierarchical data visualization via PCA trees
Hierarchical Object-Aware Dual-Level Contrastive Learning for Domain Generalized Stereo Matching
Hierarchical Visual Feature Aggregation for OCR-Free Document Understanding
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction
HOI-Swap: Swapping Objects in Videos with Hand-Object Interaction Awareness
Honor Among Bandits: No-Regret Learning for Online Fair Division
How do Large Language Models Handle Multilingualism?
How Sparse Can We Prune A Deep Network: A Fundamental Limit Perspective
How to Continually Adapt Text-to-Image Diffusion Models for Flexible Customization?
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions
HumanVid: Demystifying Training Data for Camera-controllable Human Image Animation
HumanVLA: Towards Vision-Language Directed Object Rearrangement by Physical Humanoid
HYDRA-FL: Hybrid Knowledge Distillation for Robust and Accurate Federated Learning
HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Identifying Equivalent Training Dynamics
Identifying General Mechanism Shifts in Linear Causal Representations
Identify Then Recommend: Towards Unsupervised Group Recommendation
IDGen: Item Discrimination Induced Prompt Generation for LLM Evaluation
ImageNet3D: Towards General-Purpose Object-Level 3D Understanding
Image Reconstruction Via Autoencoding Sequential Deep Image Prior
Image Understanding Makes for A Good Tokenizer for Image Generation
Immiscible Diffusion: Accelerating Diffusion Training with Noise Assignment
Implicit Regularization of Decentralized Gradient Descent for Sparse Regression
Implicit Regularization Paths of Weighted Neural Representations
Implicit Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes
Improved Algorithms for Contextual Dynamic Pricing
Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms
Improved Sample Complexity Bounds for Diffusion Model Training
Improving Adaptivity via Over-Parameterization in Sequence Models
Improving Gloss-free Sign Language Translation by Reducing Representation Density
Improving Robustness of 3D Point Cloud Recognition from a Fourier Perspective
Improving the Training of Rectified Flows
Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recovery
Infer Induced Sentiment of Comment Response to Video: A New Task, Dataset and Baseline
Infusing Synthetic Data with Real-World Patterns for Zero-Shot Material State Segmentation
In Pursuit of Causal Label Correlations for Multi-label Image Recognition
Instruction Tuning With Loss Over Instructions
Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation
InterControl: Zero-shot Human Interaction Generation by Controlling Every Joint
Interpolating Item and User Fairness in Multi-Sided Recommendations
Interpretable Machine Learning for Datasets with Missing Values
Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling
Intrinsic Self-Supervision for Data Quality Audits
Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level
IR-CM: The Fast and Universal Image Restoration Method Based on Consistency Model
Is the MMI Criterion Necessary for Explanation? Degenerating Non-causal Features to Plain Noise
John Ellipsoids via Lazy Updates
Just Add $100 More: Augmenting Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem
Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts
Knowledge-Empowered Dynamic Graph Network for Irregularly Sampled Medical Time Series
Knowledge Graph Completion by Intermediate Variables Regularization
Knowledge Graph Fine-Tuning Upon Open-World Knowledge from Large Language Models
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
Label Alignment Regularization for Distribution Shift
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
Language Hierarchical Self-training for Detecting Twenty-thousand Classes using Image-level Supervision
Large Language Model Unlearning
Large Pre-trained time series models for cross-domain Time series analysis tasks
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models
Learning and Transferring Sparse Contextual Bigrams with Linear Transformers
Learning-Augmented Dynamic Submodular Maximization
Learning-Augmented Priority Queues
Learning Better Representations From Less Data For Propositional Satisfiability
Learning Discrete Concepts in Latent Hierarchical Models
Learning Disentangled Representations for Perceptual Point Cloud Quality Assessment via Mutual Information Minimization
Learning Distributions on Manifolds with Free-Form Flows
Learning from Pattern Completion: Self-supervised Controllable Generation
Learning from Uncertain Data: From Possible Worlds to Possible Models
Learning Goal-Conditioned Representations in Reward Models for Aligning Language Models
Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms
Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient
Learning Optimal Tax Design in Nonatomic Congestion Games
Learning predictable and robust neural representations by straightening image sequences
Learning Representations for Hierarchies with Minimal Support
Learning Segmentation from Point Trajectories
Learning to Assist Humans without Inferring Rewards
Learning to Decouple the Lights for 3D Face Texture Modeling
Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers
Learning to Predict Structural Vibrations
Learning Transferable Features for Implicit Neural Representations
Learn To be Efficient: Build Structured Sparsity in Large Language Models
Leveraging Catastrophic Forgetting to Develop Safe Diffusion Models against Malicious Finetuning
Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation
LG-VQ: Language-Guided Codebook Learning
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch
Linguistic Collapse: Neural Collapse in (Large) Language Models
Linking In-context Learning in Transformers to Human Episodic Memory
LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models
LLM Evaluators Recognize and Favor Their Own Generations
Local and Adaptive Mirror Descents in Extensive-Form Games
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit
Locally Private and Robust Multi-Armed Bandits
Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
LookHere: Vision Transformers with Directed Attention Generalize and Extrapolate
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics
LOVA3: Learning to Visual Question Answering, Asking and Assessment
L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer
MAC Advice for facility location mechanism design
MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution
Make Continual Learning Stronger via C-Flat
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation
MARPLE: A Benchmark for Long-Horizon Inference
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
Mean-Field Langevin Dynamics for Signed Measures via a Bilevel Approach
Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification
MediQ: Question-Asking LLMs for Adaptive and Reliable Medical Reasoning
Med-Real2Sim: Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning
MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models
MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers
MemVLT: Vision-Language Tracking with Adaptive Memory-based Prompts
Mercury: A Code Efficiency Benchmark for Code Large Language Models
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving
Meta-Learning Universal Priors Using Non-Injective Change of Variables
Metric Flow Matching for Smooth Interpolations on the Data Manifold
Metrizing Weak Convergence with Maximum Mean Discrepancies
Mind's Eye of LLMs: Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
Mirror and Preconditioned Gradient Descent in Wasserstein Space
Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment
MixEval: Fast and Dynamic Human Preference Approximation with LLM Benchmark Mixtures
Mixture of In-Context Experts Enhance LLMs' Long Context Awareness
MM-WLAuslan: Multi-View Multi-Modal Word-Level Australian Sign Language Recognition Dataset
MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts
MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models
MonkeySee: Space-time-resolved reconstructions of natural images from macaque multi-unit activity
Monomial Matrix Group Equivariant Neural Functional Networks
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity
MotionCraft: Physics-Based Zero-Shot Video Generation
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
Multi-Group Proportional Representation
Multilingual Diversity Improves Vision-Language Representations
Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning
Multi-modal Transfer Learning between Biological Foundation Models
MultiOrg: A Multi-rater Organoid-detection Dataset
Multistable Shape from Shading Emerges from Patch Diffusion
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
Muscles in Time: Learning to Understand Human Motion In-Depth by Simulating Muscle Activations
MVSDet: Multi-View Indoor 3D Object Detection via Efficient Plane Sweeps
Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits
Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models
Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization
Neural Collapse to Multiple Centers For Imbalanced Data
Neural Cover Selection for Image Steganography
Neural Experts: Mixture of Experts for Implicit Neural Representations
Neuro-Symbolic Data Generation for Math Reasoning
Neuro-Vision to Language: Enhancing Visual Reconstruction and Language Interaction through Brain Recordings
Noise-Aware Differentially Private Regression via Meta-Learning
Noisy Label Learning with Instance-Dependent Outliers: Identifiability via Crowd Wisdom
Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery
No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests
Not All Tokens Are What You Need for Pretraining
Not Just Object, But State: Compositional Incremental Learning without Forgetting
OAM-TCD: A globally diverse dataset of high-resolution tree cover maps
ODRL: A Benchmark for Off-Dynamics Reinforcement Learning
Offline Behavior Distillation
Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression
Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting
On Affine Homotopy between Language Encoders
Once Read is Enough: Finetuning-free Language Models with Cluster-guided Sparse Experts for Long-tail Domain Knowledge
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
One for All: Multi-Domain Joint Training for Point Cloud Based 3D Object Detection
On provable privacy vulnerabilities of graph representations
On Socially Fair Low-Rank Approximation and Column Subset Selection
On Sparse Canonical Correlation Analysis
On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation
On the Inductive Bias of Stacking Towards Improving Reasoning
On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization
On the Power of Small-size Graph Neural Networks for Linear Programming
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models
On the Scalability of Certified Adversarial Robustness with Generated Data
OPEL: Optimal Transport Guided ProcedurE Learning
OpenCDA-Loop: A Closed-loop Benchmarking Platform for End-to-end Evaluation of Cooperative Perception
OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset
Optimal Algorithms for Augmented Testing of Discrete Distributions
Optimal Algorithms for Online Convex Optimization with Adversarial Constraints
Optimal deep learning of holomorphic operators between Banach spaces
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
Optimal Top-Two Method for Best Arm Identification and Fluid Analysis
Optimal Transport-based Labor-free Text Prompt Modeling for Sketch Re-identification
Optimizing Automatic Differentiation with Deep Reinforcement Learning
Ordered Momentum for Asynchronous SGD
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Overcoming Brittleness in Pareto-Optimal Learning Augmented Algorithms
OwMatch: Conditional Self-Labeling with Consistency for Open-world Semi-Supervised Learning
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
Panacea: Pareto Alignment via Preference Adaptation for LLMs
Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits
Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking
Penalty-based Methods for Simple Bilevel Optimization under Hölderian Error Bounds
Periodic agent-state based Q-learning for POMDPs
Permutation-Invariant Autoregressive Diffusion for Graph Generation
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning
PhoCoLens: Photorealistic and Consistent Reconstruction in Lensless Imaging
Physically Compatible 3D Object Modeling from a Single Image
Pick up the PACE: A Parameter-Free Optimizer for Lifelong Reinforcement Learning
PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models
PIVOT-R: Primitive-Driven Waypoint-Aware World Model for Robotic Manipulation
Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs
PLIP: Language-Image Pre-training for Person Representation Learning
Post-Robustness of Backdoor Purification
Precipitation Downscaling with Spatiotemporal Video Diffusion
Predicting Future Actions of Reinforcement Learning Agents
Prediction with Action: Visual Policy Learning via Joint Denoising Process
Prejudice and Volatility: A Statistical Framework for Measuring Social Discrimination in Large Language Models
Pre-Trained Multi-Goal Transformers with Prompt Optimization for Efficient Online Adaptation
Principled Bayesian Optimization in Collaboration with Human Experts
Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs
PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action
Probabilistic Federated Prompt-Tuning in Data Imbalance Settings
Probablistic Emulation of a Global Climate Model with Spherical DYffusion
Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models
PromptFix: You Prompt and We Fix the Photo
Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation
Propensity Score Alignment of Unpaired Multimodal Data
PROSPECT PTMs: Rich Labeled Tandem Mass Spectrometry Dataset of Modified Peptides for Machine Learning in Proteomics
Protecting Your LLMs with Information Bottleneck
ProTransformer: Robustify Transformers via Plug-and-Play Paradigm
Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks
Provable Guarantees for Model Performance via Mechanistic Intepretability
Provable Partially Observable Reinforcement Learning with Privileged Information
Prune and Repaint: Content-Aware Image Retargeting for any Ratio
Pure Message Passing Can Estimate Common Neighbor for Link Prediction
PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression
QGFN: Controllable Greediness with Action Values
QTIP: Quantization with Trellises and Incoherence Processing
Qualitative Mechanism Independence
Questioning the Survey Responses of Large Language Models
R$^2$-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction
RadarOcc: Robust 3D Occupancy Prediction with 4D Imaging Radar
Rad-NeRF: Ray-decoupled Training of Neural Radiance Field
RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations
Random Function Descent
Randomized Minor-Value Rectification: A Novel Matrix Sparsification Algorithm for Solving Constrained Optimizations in Cancer Radiation Therapy
Randomized Strategic Facility Location with Predictions
Randomized Truthful Auctions with Learning Agents
RashomonGB: Analyzing the Rashomon Effect and Mitigating Predictive Multiplicity in Gradient Boosting
Reciprocal Learning
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
Recurrent neural networks: vanishing and exploding gradients are not the end of the story
Recurrent Reinforcement Learning with Memoroids
[Re] Explaining Temporal Graph Models through an Explorer-Navigator Framework
Regret Minimization in Stackelberg Games with Side Information
Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers
Reinforcement Learning with LTL and $\omega$-Regular Objectives via Optimality-Preserving Translation to Average Rewards
Reinforcing Language Agents via Policy Optimization with Action Decomposition
Relation-Driven Diffusion for Human-Object Interaction Detection
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization
Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing
Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach
Reproducibility Study: Equal Improvability: A New Fairness Notion Considering the Long-Term Impact
Reproducibility Study of "ITI-GEN: Inclusive Text-to-Image Generation"
Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers
Reranking Laws for Language Generation: A Communication-Theoretic Perspective
Resource-Aware Federated Self-Supervised Learning with Global Class Representations
Rethinking 3D Convolution in $\ell_p$-norm Space
Rethinking Deep Thinking
Return of Unconditional Generation: A Self-supervised Representation Generation Method
ReVideo: Remake a Video with Motion and Content Control
Revisiting Score Propagation in Graph Out-of-Distribution Detection
ReXTime: A Benchmark Suite for Reasoning-Across-Time in Videos
RGFN: Synthesizable Molecular Generation Using GFlowNets
Right this way: Can VLMs Guide Us to See More to Answer Questions?
Risk-sensitive control as inference with Rényi divergence
RoboMamba: Multimodal State Space Model for Efficient Robot Reasoning and Manipulation
Robust Contrastive Multi-view Clustering against Dual Noisy Correspondence
Robust Sleep Staging over Incomplete Multimodal Physiological Signals via Contrastive Imagination
RoPINN: Region Optimized Physics-Informed Neural Networks
RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models
RTify: Aligning Deep Neural Networks with Human Behavioral Decisions
Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage
Sample-Efficient Agnostic Boosting
SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection
ScaleKD: Strong Vision Transformers Could Be Excellent Teachers
Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
Schedule Your Edit: A Simple yet Effective Diffusion Noise Schedule for Image Editing
SciCode: A Research Coding Benchmark Curated by Scientists
Scientific Consistency Improves upon Multi-Task Learning in Molecular Science
Score Distillation via Reparametrized DDIM
SDformer: Similarity-driven Discrete Transformer For Time Series Generation
Secret Collusion among Generative AI Agents
Segmenting Watermarked Texts From Language Models
SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations
Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
Sharing Key Semantics in Transformer Makes Efficient Image Restoration
Sim2Real-Fire: A Multi-modal Simulation Dataset for Forecast and Backtracking of Real-world Forest Fire
Simple and Effective Masked Diffusion Language Models
Sim-to-Real Transfer Can Make Naive Exploration Efficient in Reinforcement Learning
Simulation-Free Training of Neural ODEs on Paired Data
Single Forward Video Generation Model
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models
Sketching for Distributed Deep Learning: A Sharper Analysis
SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection
SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining
SM3-Text-to-Query: Synthetic Multi-Model Medical Text-to-Query Benchmark
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates
Smoke and Mirrors in Causal Downstream Tasks
Solving Intricate Problems with Human-like Decomposition and Rethinking
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
Sparse High Rank Adapters
Spectral Editing of Activations for Large Language Model Alignment
Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?
Spike-based Neuromorphic Model for Sound Source Localization
S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization
Stabilized Proximal Point Methods for Federated Optimization
Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks
Statistical Multicriteria Benchmarking via the GSD-Front
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution
Stochastic Optimal Control for Diffusion Bridges in Function Spaces
Stylebreeder: Exploring and Democratizing Artistic Styles through Text-to-Image Models
Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning
SuperVLAD: Compact and Robust Image Descriptors for Visual Place Recognition
Supra-Laplacian Encoding for Transformer on Dynamic Graphs
SurgicAI: A Fine-grained Platform for Data Collection and Benchmarking in Surgical Policy Learning
SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention
Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition
T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback
TableRAG: Million-Token Tabular Reasoning with Large Language Models
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
TAPVid-3D: A Benchmark for Tracking Any Point in 3D
Targeted Sequential Indirect Experiment Design
Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions
TaskBench: Benchmarking Large Language Models for Task Automation
Task-oriented Time Series Imputation Evaluation via Generalized Representers
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning
Test-Time Dynamic Image Fusion
Tetrahedron Splatting for 3D Generation
TFG: Unified Training-Free Guidance for Diffusion Models
The Art of Saying No: Contextual Noncompliance in Language Models
The Bayesian sampling in a canonical recurrent circuit with a diversity of inhibitory interneurons
The Benefits of Balance: From Information Projections to Variance Reduction
The Convergence of Variance Exploding Diffusion Models under the Manifold Hypothesis
The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing
Theoretical Foundations of Deep Selective State-Space Models
The Prevalence of Neural Collapse in Neural Multivariate Regression
The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding
The Space Complexity of Approximating Logistic Loss
The State of Data Curation at NeurIPS: An Assessment of Dataset Development Practices in the Datasets and Benchmarks Track
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
Thought of Search: Planning with Language Models Through The Lens of Efficiency
Tight Bounds for Learning RUMs from Small Slates
Tight Rates for Bandit Control Beyond Quadratics
Time-Reversal Provides Unsupervised Feedback to LLMs
TopoFR: A Closer Look at Topology Alignment on Face Recognition
Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms
Topological Hidden Markov Models
Toward Approaches to Scalability in 3D Human Pose Estimation
Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution
Towards Comprehensive Detection of Chinese Harmful Memes: Dataset and Detector
Towards Evaluation of Adversarial Robustness and Privacy on Label Mapping Visual Prompting Models
Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation
Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model
Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration
TPR: Topology-Preserving Reservoirs for Generalized Zero-Shot Learning
TrAct: Making First-layer Pre-Activations Trainable
Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming
Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy
Trajectory Volatility for Out-of-Distribution Detection in Mathematical Reasoning
Transcendence: Generative Models Can Outperform The Experts That Train Them
Transfer Learning for Latent Variable Network Models
Transfer Q-star : Principled Decoding for LLM Alignment
Transformers on Markov data: Constant depth suffices
Tree of Attacks: Jailbreaking Black-Box LLMs Automatically
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
Turning Indirect Knowledge into Direct Demonstrations for Computer Agents at Scale
UDON: Universal Dynamic Online distillatioN for generic image representations
Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs
Unchosen Experts Can Contribute Too: Unleashing MoE Models’ Power by Self-Contrast
Understanding Model Selection for Learning in Strategic Environments
UniDSeg: Unified Cross-Domain 3D Semantic Segmentation via Visual Foundation Models Prior
UniFL: Improve Stable Diffusion via Unified Feedback Learning
Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
United We Stand, Divided We Fall: Fingerprinting Deep Neural Networks via Adversarial Trajectories
UNITS: A Unified Multi-Task Time Series Model
Universal In-Context Approximation By Prompting Fully Recurrent Models
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
Universal Rates for Active Learning
Unleashing Multispectral Video's Potential in Semantic Segmentation: A Semi-supervised Viewpoint and New UAV-View Benchmark
Unlocking the Boundaries of Thought: A Reasoning Granularity Framework to Quantify and Optimize Chain-of-Thought
Unrolled denoising networks that provably learn to perform optimal Bayesian inference
Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need?
Unsupervised Homography Estimation on Multimodal Image Pair via Alternating Optimization
Untrained Neural Nets for Snapshot Compressive Imaging: Theory and Algorithms
Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization
Unveiling Encoder-Free Vision-Language Models
Unveiling LoRA Intrinsic Ranks via Salience Analysis
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
Unveiling the Tapestry of Consistency in Large Vision-Language Models
User-item fairness tradeoffs in recommendations
Using Unity to Help Solve Reinforcement Learning
Utilizing Human Behavior Modeling to Manipulate Explanations in AI-Assisted Decision Making: The Good, the Bad, and the Ugly
Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting
VHELM: A Holistic Evaluation of Vision Language Models
VideoGUI: A Benchmark for GUI Automation from Instructional Videos
Video Token Merging for Long Video Understanding
ViLCo-Bench: VIdeo Language COntinual learning Benchmark
VISA: Variational Inference with Sequential Sample-Average Approximations
Vision-Language Navigation with Energy-Based Policy
Vision Mamba Mender
VLMimic: Vision Language Models are Visual Imitation Learner for Fine-grained Actions
V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark
Warm-starting Push-Relabel
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents
Weight decay induces low-rank attention layers
What If the Input is Expanded in OOD Detection?
What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks
When does perceptual alignment benefit vision representations?
When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models
When to Act and When to Ask: Policy Learning With Deferral Under Hidden Confounding
Why Transformers Need Adam: A Hessian Perspective
WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia
WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata
WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences
Wormhole Loss for Partial Shape Matching
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology
You Only Look Around: Learning Illumination-Invariant Feature for Low-light Object Detection
μBench: A Microscopy Benchmark for Vision-Language Understanding
(ends 2:00 PM)
Creative AI Session 5 [11:00-11:03]
(ends 11:03 AM)
1 p.m.
Break:
Lunch Break
(ends 2:30 PM)
2:30 p.m.
Invited Talk:
Invited Talk - Arnaud Doucet
Arnaud Doucet
(ends 3:30 PM)
3:30 p.m.
Oral Session 4A [3:30-4:30]
DevBench: A multimodal developmental benchmark for language learning
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages
(ends 4:30 PM)
Oral Session 4B [3:30-4:30]
CAT3D: Create Anything in 3D with Multi-View Diffusion Models
Stylus: Automatic Adapter Selection for Diffusion Models
Guiding a Diffusion Model with a Bad Version of Itself
(ends 4:30 PM)
Oral Session 4C [3:30-4:30]
DenoiseReID: Denoising Model for Representation Learning of Person Re-Identification
Improved Distribution Matching Distillation for Fast Image Synthesis
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
(ends 4:30 PM)
Oral Session 4D [3:30-4:30]
Gaussian-Informed Continuum for Physical Property Identification and Simulation
MeshFormer : High-Quality Mesh Generation with 3D-Guided Reconstruction Model
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection
(ends 4:30 PM)
4:30 p.m.
Poster Session 4 [4:30-7:30]
Posters 4:30-7:30
A Framework for Bilevel Optimization on Riemannian Manifolds
A Polar Coordinate System Explicitly Represents Syntax in Language Models
Association Pattern-aware Fusion for Biological Entity Relationship Prediction
Black-Box Forgetting
Capability v.s. Behavior in Compositional Generalization: A Learning Dynamics Perspective
Continual Learning in the Frequency Domain
CountGD: Multi-Modal Open-World Counting
DDGS-CT: Direction-Disentangled Gaussian Splatting for Realistic Volume Rendering
Dense Associative Memory Through the Lens of Random Features
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks
Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections
Expectile Regularization for Fast and Accurate Training of Neural Optimal Transport
Fair Allocation in Dynamic Mechanism Design
First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion
How to Boost Any Loss Function
Long-form factuality in large language models
Mixture of Experts Meets Prompt-Based Continual Learning
On the Computational Complexity of Private High-dimensional Model Selection
Optimal Hypothesis Selection in (Almost) Linear Time
The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure
Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?
$\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
$\text{ID}^3$: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition
$\texttt{Model-GLUE}$: Democratized LLM Scaling for A Large Model Zoo in the Wild
3D Equivariant Pose Regression via Direct Wigner-D Harmonics Prediction
A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings
Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification
Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
Accelerated Regularized Learning in Finite N-Person Games
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity
Accelerating ERM for data-driven algorithm design using output-sensitive techniques
Accelerating Non-Maximum Suppression: A Graph Theory Perspective
Accurate and Steady Inertial Pose Estimation through Sequence Structure Learning and Modulation
Achieving Linear Convergence with Parameter-Free Algorithms in Decentralized Optimization
A Comprehensive Investigation of Sparse Rate Reduction in Transformer-like Models
Active, anytime-valid risk controlling prediction sets
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
Adaptive Exploration for Data-Efficient General Value Function Evaluations
Adaptive Passive-Aggressive Framework for Online Regression with Side Information
Addressing Asynchronicity in Clinical Multimodal Fusion via Individualized Chest X-ray Generation
Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
Adjust Pearson's $r$ to Measure Nonlinear Monotone Dependence
ADOPT: Modified Adam Can Converge with Any $\beta_2$ with the Optimal Rate
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation
Advantage-Aware Policy Optimization for Offline Reinforcement Learning
Adversarial Robust Decision Transformer: Enhancing RvS Robustness via Minimax Returns
A Functional Extension of Semi-Structured Networks
AgentGym: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents
A Hitchhikers Guide to Fine-Grained Face Forgery Detection Using Common Sense Reasoning
A Label is Worth A Thousand Images in Dataset Distillation
Aligning LLM Agents by Learning Latent Preference from User Edits
Alignment for Honesty
Alleviating Attention Bias for Visual-Informed Text Generation
ALS: Adaptive Layer Sparsity for Large Language Models via Activation Correlation Assessment
Amortized Fourier Neural Operators
Amortizing intractable inference in diffusion models for vision, language, and control
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
Analyzing & Reducing the Need for Learning Rate Warmup in Neural Network Optimization
An End-To-End Graph Attention Network Hash for Cross-Modal Retrieval
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization
Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss
APDDv2: Aesthetics of Paintings and Drawings Dataset with Artist Labeled Scores and Comments
A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention
A PID Controller Approach for Adaptive Probability-dependent Gradient Decay in Model Calibration
Approaching Human-Level Forecasting with Language Models
Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient
Approximation Rate of the Transformer Architecture for Sequence Modeling
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?
Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?
Are Self-Attentions Effective for Time Series Forecasting?
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction
AR-Pro: Anomaly Explanation and Repair with Formal Properties
A scalable generative model for dynamical system reconstruction from neuroimaging data
A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations
A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training
Ask, Attend, Attack: A Effective Decision-Based Black-Box Targeted Attack for Image-to-Text Models
A StrongREJECT for Empty Jailbreaks
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences
AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising
Attack-Aware Noise Calibration for Differential Privacy
A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems
A Universal Growth Rate for Learning with Smooth Surrogate Losses
AutoMix: Automatically Mixing Language Models
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
AV-GS: Learning Material and Geometry Aware Priors for Novel View Acoustic Synthesis
BackTime: Backdoor Attacks on Multivariate Time Series Forecasting
Banded Square Root Matrix Factorization for Differentially Private Model Training
Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs
Bandits with Ranking Feedback
Barely Random Algorithms for Metrical Task Systems
Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing
Bayesian Online Natural Gradient (BONG)
BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
Benchmarking Complex Instruction-Following with Multiple Constraints Composition
Benchmarking Out-of-Distribution Generalization and Adaptation for Electromyography
Benchmarking Structural Inference Methods for Interacting Dynamical Systems with Synthetic Data
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
Better by default: Strong pre-tuned MLPs and boosted trees on tabular data
Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection
Binocular-Guided 3D Gaussian Splatting with View Consistency for Sparse View Synthesis
BonBon Alignment for Large Language Models: on the Sweetness of Best-of-n Sampling
BoostAdapter: Improving Test-Time Adaptation via regional boostraping
Boosting Vision-Language Models with Transduction
Bridge the Modality and Capacity Gaps in Vision-Language Model Selection
Bridge the Points: Graph-based Few-shot Segment Anything Semantically
Bridging the Divide: Reconsidering Softmax and Linear Attention
Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
CALANet: Cheap All-Layer Aggregation for Human Activity Recognition
CALE: Continuous Arcade Learning Environment
Calibrated Self-Rewarding Vision Language Models
Can large language models explore in-context?
CAT3D: Create Anything in 3D with Multi-View Diffusion Models
CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense
Causal Imitation for Markov Decision Processes: a Partial Identification Approach
CausalStock: Deep End-to-end Causal Discovery for News-driven Multi-stock Movement Prediction
Causal vs. Anticausal merging of predictors
Cell ontology guided transcriptome foundation model
Certified Machine Unlearning via Noisy Stochastic Gradient Descent
Chain-of-Thought Unfaithfulness as Disguised Accuracy
Challenges of Generating Structurally Diverse Graphs
ChronoMagic: A Benchmark for Metamorphic Evaluation of Time-lapse Text-to-Video Generation
CIFD: Controlled Information Flow to Enhance Knowledge Distillation
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification
CLIPAway: Harmonizing focused embeddings for removing objects via diffusion models
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning
Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding
CNCA: Toward Customizable and Natural Generation of Adversarial Camouflage for Vehicle Detectors
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
COLD: Causal reasOning in cLosed Daily activities
ComBack: A Versatile Dataset for Enhancing Compiler Backend Development Efficiency
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification
CoMERA: Computing- and Memory-Efficient Training via Rank-Adaptive Tensor Optimization
Compute-efficient LLM Training via Online Batch Selection
Computerized Adaptive Testing via Collaborative Ranking
ConceptFactory: Facilitate 3D Object Knowledge Annotation with Object Conceptualization
ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty
Conditional Synthesis of 3D Molecules with Time Correction Sampler
Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness
Constrained Binary Decision Making
Constrained Diffusion with Trust Sampling
Constrained Sampling with Primal-Dual Langevin Monte Carlo
Context-aware testing: A new paradigm for tabular model testing
Contextual Decision-Making with Knapsacks beyond the Worst Case
Contextual Linear Optimization with Bandit Feedback
Continual learning with the neural tangent ensemble
Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Crafting Hierarchical Strand-based Hair Geometry with Frequency-decomposed Representative Guide Curves
Credal Learning Theory
CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph
DarkSAM: Fooling Segment Anything Model to Segment Nothing
Data-Driven Discovery of Dynamical Systems in Pharmacology using Large Language Models
Data-Efficient Learning with Neural Programs
Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions
Data subsampling for Poisson regression
Dealing with Synthetic Data Contamination in Online Continual Learning
Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
DenoiseReID: Denoising Model for Representation Learning of Person Re-Identification
DEPrune: Depth-wise Separable Convolution Pruning for Maximizing GPU Parallelism
Depth Anything V2
Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers
DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ
DevBench: A multimodal developmental benchmark for language learning
Differentiable Task Graph Learning: Procedural Activity Representation and Online Mistake Detection from Egocentric Videos
DiffuLT: Diffusion for Long-tail Recognition Without External Knowledge
Diffusion Actor-Critic with Entropy Regulator
Diffusion-based Curriculum Reinforcement Learning
Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization
Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
Diffusion Model-based Numerical Tabular Data Imputation: A Wasserstein Gradient Flow Perspective
Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement
Diffusion PID: Interpreting Diffusion via Partial Information Decomposition
Directional Smoothness and Gradient Methods: Convergence and Adaptivity
DisCEdit: Model Editing by Identifying Discriminative Components
Discovering Sparsity Allocation for Layer-wise Pruning of Large Language Models
Discovery of the Hidden World with Large Language Models
DiscoveryWorld: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents
Discretely beyond $1/e$: Guided Combinatorial Algortihms for Submodular Maximization
Disentangling Linear Quadratic Control with Untrusted ML Predictions
Distributional Reinforcement Learning with Regularized Wasserstein Loss
Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment
Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners
D-LLM: A Token Adaptive Computing Resource Allocation Strategy for Large Language Models
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD
DoFIT: Domain-aware Federated Instruction Tuning with Alleviated Catastrophic Forgetting
DomainGallery: Few-shot Domain-driven Image Generation by Attribute-centric Finetuning
Do Multimodal Foundation Models Understand Enterprise Workflows? A Benchmark for Business Process Management Tasks
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
DP-SGD with Fixed-Size Minibatches: Tighter Guarantees with or without Replacement
Dual Encoder GAN Inversion for High-Fidelity 3D Head Reconstruction from Single Images
DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation
Dynamic Neural Regeneration: Enhancing Deep Learning Generalization on Small Datasets
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection
Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization
Easy Regional Contrastive Learning of Expressive Visual Fashion Representations
Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
EffiBench: Benchmarking the Efficiency of Automatically Generated Code
Efficient Centroid-Linkage Clustering
Efficient Combinatorial Optimization via Heat Diffusion
Efficient Convex Algorithms for Universal Kernel Learning
Efficient Discrepancy Testing for Learning with Distribution Shift
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization
Efficient Multi-modal Models via Stage-wise Visual Context Compression
Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters
Efficient Pipeline Parallelism with Controllable Memory
Efficient Streaming Algorithms for Graphlet Sampling
EGSST: Event-based Graph Spatiotemporal Sensitive Transformer for Object Detection
EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries
einspace: Searching for Neural Architectures from Fundamental Operations
Elliptical Attention
Embedding-Aligned Language Models
Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning
Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism
Emu3D: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials
EMVP: Embracing Visual Foundation Model for Visual Place Recognition with Centroid-Free Probing
Enhancing Domain Adaptation through Prompt Gradient Alignment
Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
Enriching Disentanglement: From Logical Definitions to Quantitative Metrics
Episodic Future Thinking Reinforcement Learning for Social Decision-making
ESPACE: Dimensionality Reduction of Activations for Model Compression
Evaluate then Cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering
Evaluating the World Model Implicit in a Generative Model
Evidence of Learned Look-Ahead in a Chess-Playing Neural Network
EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models
Expanding Sparse Tuning for Low Memory Usage
Exploring DCN-like architecture for fast image generation with arbitrary resolution
Exploring & Improving Multi-token Prediction (Block Draft) in Language Modeling
eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling
Extracting Training Data from Molecular Pre-trained Models
EyeGraph: Modularity-aware Spatio Temporal Graph Clustering for Continuous Event-based Eye Tracking
FairWire: Fair Graph Generation
Fast Encoder-Based 3D from Casual Videos via Point Track Processing
Faster Differentially Private Top-$k$ Selection: A Joint Exponential Mechanism with Pruning
Faster Local Solvers for Graph Diffusion Equations
Fast Sampling via Discrete Non-Markov Diffusion Models
Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
Federated Graph Learning for Cross-Domain Recommendation
Federated Learning over Connected Modes
FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Privacy-Preserving Dimensionality Reduction
FEEL-SNN: Robust Spiking Neural Networks with Frequency Encoding and Evolutionary Leak Factor
Fetch and Forge: Efficient Dataset Condensation for Object Detection
Few-Shot Diffusion Models Escape the Curse of Dimensionality
Few-Shot Task Learning Through Inverse Generative Modeling
FIFO-Diffusion: Generating Infinite Videos from Text without Training
Fight Back Against Jailbreaking via Prompt Adversarial Tuning
Finding good policies in average-reward Markov Decision Processes without prior knowledge
Fine-Tuning is Fine, if Calibrated
Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination
FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models
Fixed points of nonnegative neural networks
Flaws can be Applause: Unleashing Potential of Segmenting Ambiguous Objects in SAM
Flexible Context-Driven Sensory Processing in Dynamical Vision Models
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
FM-Delta: Lossless Compression for Storing Massive Fine-tuned Foundation Models
Foundation Inference Models for Markov Jump Processes
Fourier Amplitude and Correlation Loss: Beyond Using L2 loss for Skillful Precipitation Nowcasting
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach
From Chaos to Clarity: 3DGS in the Dark
From Transparent to Opaque: Rethinking Neural Implicit Surfaces with $\alpha$-NeuS
FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning
Full-Distance Evasion of Pedestrian Detectors in the Physical World
FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding
GAIA: Rethinking Action Quality Assessment for AI-Generated Videos
GAMap: Zero-Shot Object Goal Navigation with Multi-Scale Geometric-Affordance Guidance
Gated Inference Network: Inferencing and Learning State-Space Models
Gated Slot Attention for Efficient Linear-Time Sequence Modeling
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning
Gaussian-Informed Continuum for Physical Property Identification and Simulation
GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing
Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts
Generated and Pseudo Content guided Prototype Refinement for Few-shot Point Cloud Segmentation
Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
Generating compositional scenes via Text-to-image RGBA Instance Generation
Generating Highly Designable Proteins with Geometric Algebra Flow Matching
Generative Adversarial Bayesian Optimization for Surrogate Objectives
Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables
GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping
Geometry of naturalistic object representations in recurrent neural network models of working memory
Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning
GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning
GLBench: A Comprehensive Benchmark for Graph with Large Language Models
GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI
GPT as Visual Explainer
Graph Classification via Reference Distribution Learning: Theory and Practice
Grasp as You Say: Language-guided Dexterous Grasp Generation
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
Group and Shuffle: Efficient Structured Orthogonal Parametrization
GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations
Guiding a Diffusion Model with a Bad Version of Itself
Hallo3D: Multi-Modal Hallucination Detection and Mitigation for Consistent 3D Content Generation
HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection
Happy: A Debiased Learning Framework for Continual Generalized Category Discovery
Harnessing Heuristics for Deep Reinforcement Learning via Constrained Optimization
Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models
HelpSteer 2: Open-source dataset for training top-performing reward models
HENASY: Learning to Assemble Scene-Entities for Interpretable Egocentric Video-Language Model
Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees
HOPE: Shape Matching Via Aligning Different K-hop Neighbourhoods
HourVideo: 1-Hour Video-Language Understanding
How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization?
How to Use Diffusion Priors under Sparse Views?
Humanoid Locomotion as Next Token Prediction
HYDRA: Model Factorization Framework for Black-Box LLM Personalization
HydraViT: Stacking Heads for a Scalable ViT
Hyperbolic Embeddings of Supervised Models
Hyper-opinion Evidential Deep Learning for Out-of-Distribution Detection
Hypothesis Testing the Circuit Hypothesis in LLMs
HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis
Identifying and Solving Conditional Image Leakage in Image-to-Video Generation
Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models
ID-to-3D: Expressive ID-guided 3D Heads via Score Distillation Sampling
ImageNet++: A Large-Scale Benchmark of Data Curation Strategies
IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localization
Imitating Language via Scalable Inverse Reinforcement Learning
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient
Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problems
Improved Distribution Matching Distillation for Fast Image Synthesis
Improved Regret for Bandit Convex Optimization with Delayed Feedback
Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders
Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity
IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark
In-Context Learning with Representations: Contextual Generalization of Trained Transformers
Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques
Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence
Inference on the Change Point under a High Dimensional Covariance Shift
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory
Information-theoretic Limits of Online Classification with Noisy Labels
InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling
Infusing Self-Consistency into Quantum Hamiltonian Prediction via Deep Equilibrium Models
Initializing Variable-sized Vision Transformers from Learngene with Learnable Transformations
Input-to-State Stable Coupled Oscillator Networks for Closed-form Model-based Control in Latent Space
Instance-Optimal Private Density Estimation in the Wasserstein Distance
Instruction-Guided Visual Masking
Instructor-inspired Machine Learning for Robust Molecular Property Prediction
Interaction-Force Transport Gradient Flows
Interventional Causal Discovery in a Mixture of DAGs
Interventionally Consistent Surrogates for Complex Simulation Models
Invariant subspaces and PCA in nearly matrix multiplication time
InversionView: A General-Purpose Method for Reading Information from Neural Activations
IPO: Interpretable Prompt Optimization for Vision-Language Models
IQA-EVAL: Automatic Evaluation of Human-Model Interactive Question Answering
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning
Is Programming by Example solved by LLMs?
Is Value Function Learning Really the Main Bottleneck of Offline RL?
Iterative Reasoning Preference Optimization
iVideoGPT: Interactive VideoGPTs are Scalable World Models
IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing
KnowGPT: Knowledge Graph based Prompting for Large Language Models
Knowledge Circuit in Transformers
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks
Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping
L4GM: Large 4D Gaussian Reconstruction Model
LaKD: Length-agnostic Knowledge Distillation for Trajectory Prediction with Any Length Observations
Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Cases
Language-Driven Interactive Traffic Trajectory Generation
Language Generation in the Limit
Language Grounded Multi-Agent Communication for Ad-hoc Teamwork
Language Without Borders: A Dataset and Benchmark for Code-Switching Lip Reading
Large Language Model-Driven Audio Codec is a Few-Shot Audio Task Learner
Large Language Models as Hyper-Heuristics for Combinatorial Optimization
Large Scale Transfer Learning for Tabular Data via Language Modeling
LAVIB: A Large-scale Video Interpolation Benchmark
Learnability Matters: Active Learning for Video Captionin
Learnable In-Context Vector for Visual Question Answering
Learning Bregman Divergences with Application to Robustness
Learning Cooperative Trajectory Representations for Motion Forecasting
Learning Cut Generating Functions for Integer Programming
Learning De-Biased Representations for Remote-Sensing Imagery
Learning Discrete Latent Variable Structures with Tensor Rank Conditions
Learning Distinguishable Trajectory Representation with Contrastive Loss
Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem
Learning Human-like Representations to Enable Learning Human Values
Learning Identifiable Factorized Causal Representations of Cellular Responses
Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Learning Mixtures of Unknown Causal Interventions
Learning Successor Features the Simple Way
Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching
Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios
Learning World Models for Unconstrained Goal Navigation
Least Squares Regression Can Exhibit Under-Parameterized Double Descent
Length Optimization in Conformal Prediction
Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals
Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers
Light Unbalanced Optimal Transport
Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
Limits of Transformer Language Models on Learning to Compose Algorithms
Linearly Decomposing and Recomposing Vision Transformers for Diverse-Scale Models
Linear Time Approximation Algorithm for Column Subset Selection with Local Search
LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages
LLaNA: Large Language and NeRF Assistant
LLMs Can Evolve Continually on Modality for $\mathbb{X}$-Modal Reasoning
LocCa: Visual Pretraining with Location-aware Captioners
LoFiT: Localized Fine-tuning on LLM Representations
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation
Long-range Brain Graph Transformer
Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
LoQT: Low Rank Adapters for Quantized Training
Loss Symmetry and Noise Equilibrium of Stochastic Gradient Descent
Low Degree Hardness for Broadcasting on Trees
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Models
LuSh-NeRF: Lighting up and Sharpening NeRFs for Low-light Scenes
MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization
MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization
MambaLRP: Explaining Selective State Space Sequence Models
MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts
MAN TruckScenes: A multimodal dataset for autonomous trucking in diverse conditions
Map It Anywhere: Empowering BEV Map Prediction using Large-scale Public Datasets
MaVEn: An Effective Multi-granularity Hybrid Visual Encoding Framework for Multimodal Large Language Model
MeMo: Meaningful, Modular Controllers via Noise Injection
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
MEQA: A Benchmark for Multi-hop Event-centric Question Answering with Explanations
Mesa-Extrapolation: A Weave Position Encoding Method for Enhanced Extrapolation in LLMs
MeshFormer : High-Quality Mesh Generation with 3D-Guided Reconstruction Model
Meta-Diffu$B$: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-Exploration
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence
Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making
MiSO: Optimizing brain stimulation to create neural activity states
Mitigating Covariate Shift in Behavioral Cloning via Robust Distribution Correction Estimation
Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes
Mixture of Adversarial LoRAs: Boosting Robust Generalization in Meta-tuning
Mixture of Demonstrations for In-Context Learning
Mixtures of Experts for Audio-Visual Learning
MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation
Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration
Model-Based Transfer Learning for Contextual Reinforcement Learning
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
MoVA: Adapting Mixture of Vision Experts to Multimodal Context
Moving Off-the-Grid: Scene-Grounded Video Representations
MQT-LLaVA: Matryoshka Query Transformer for Large Vision-Language Models
Multiclass Transductive Online Learning
Multi-Head Mixture-of-Experts
Multi-Instance Partial-Label Learning with Margin Adjustment
Mutual Information Estimation via Normalizing Flows
MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encoding
MV2Cyl: Reconstructing 3D Extrusion Cylinders from Multi-View Images
Nearest Neighbor Speculative Decoding for LLM Generation and Attribution
Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model
NeoRL: Efficient Exploration for Nonepisodic RL
Neur2BiLO: Neural Bilevel Optimization
Neural Embedding Ranks: Aligning 3D latent dynamics with movement for long-term and cross-area decoding
Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses
NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolation
No Free Delivery Service: Epistemic limits of passive data collection in complex social systems
Nonlinear dynamics of localization in neural receptive fields
Normal-GS: 3D Gaussian Splatting with Normal-Involved Rendering
Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features
NYU CTF Dataset: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security
OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queries
Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
Oja's Algorithm for Sparse PCA
OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents
On conditional diffusion models for PDE simulations
One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection
Online Adaptation of Language Models with a Memory of Amortized Contexts
Online Classification with Predictions
Online Posterior Sampling with a Diffusion Prior
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?
On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidance
On the Necessity of Collaboration for Online Model Selection with Decentralized Data
On the Power of Decision Trees in Auto-Regressive Language Modeling
On the Reproducibility of: "Learning Perturbations to Explain Time Series Predictions"
On the Role of Attention Masks and LayerNorm in Transformers
On Tractable $\Phi$-Equilibria in Non-Concave Games
Open-Book Neural Algorithmic Reasoning
Open LLMs are Necessary for Private Adaptations and Outperform their Closed Alternatives
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
Operator World Models for Reinforcement Learning
Opponent Modeling with In-context Search
OptCM: The Optimization Consistency Models for Solving Combinatorial Problems in Few Shots
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations
Optimal Batched Best Arm Identification
Optimal Clustering with Bandit Feedback
Optimal Scalarizations for Sublinear Hypervolume Regret
Optimization-based Causal Estimation from Heterogeneous Environments
Optimization Can Learn Johnson Lindenstrauss Embeddings
Optimization Efficient Open-World Visual Region Recognition
Oracle-Efficient Reinforcement Learning for Max Value Ensembles
OSLO: One-Shot Label-Only Membership Inference Attacks
OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation
Overfitting Behaviour of Gaussian Kernel Ridge Regression: Varying Bandwidth or Dimensionality
Paths to Equilibrium in Games
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning
Perception of Knowledge Boundary for Large Language Models through Semi-open-ended Question Answering
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator
Persistence Homology Distillation for Semi-supervised Continual Learning
Persistent Test-time Adaptation in Recurring Testing Scenarios
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations
Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization
Plant-and-Steal: Truthful Fair Allocations via Predictions
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection
PointMamba: A Simple State Space Model for Point Cloud Analysis
Poisson Variational Autoencoder
Policy Improvement using Language Feedback Models
Polyak Meets Parameter-free Clipped Gradient Descent
PowerGraph: A power grid benchmark dataset for graph neural networks
Practical Guide for Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization
Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms
Preference Learning Algorithms Do Not Learn Preference Rankings
Pretrained Large Language Models Use Fourier Features to Compute Addition
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control
Pre-training Differentially Private Models with Limited Public Data
Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization
Progressive Cross-Scale Self-Supervised Blind Image Deconvolution via Implicit Neural Representation
Progressive Exploration-Conformal Learning for Sparsely Annotated Object Detection in Aerial Images
Prospective Learning: Learning for a Dynamic Future
Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction
Provably Safe Neural Network Controllers via Differential Dynamic Logic
ProxyFusion: Face Feature Aggregation Through Sparse Experts
PuLID: Pure and Lightning ID Customization via Contrastive Alignment
PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling
QBB: Quantization with Binary Bases for LLMs
Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model
QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers
QKFormer: Hierarchical Spiking Transformer using Q-K Attention
Quadratic Quantum Variational Monte Carlo
Quantifying the Bitter Lesson: How Safety Benchmarks Measure Capabilities Instead of Safety
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation
Queueing Matching Bandits with Preference Feedback
Q-VLM: Post-training Quantization for Large Vision-Language Models
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning
RankRAG: Unifying Retrieval-Augmented Generation and Context Ranking in LLMs
RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modeling
realSEUDO for real-time calcium imaging analysis
Real-world Image Dehazing with Coherence-based Pseudo Labeling and Cooperative Unfolding Network
Reasons and solutions for the decline in model performance after editing
[Re] Classwise-Shapley values for data valuation
Reconstructing the Image Stitching Pipeline: Integrating Fusion and Rectangling into a Unified Inpainting Model
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery
Recurrent neural network dynamical systems for biological vision
RedCode: Multi-dimensional Safety Benchmark for Code Agents
Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network
Reinforcement Learning with Adaptive Control Regularization for Safe Control of Critical Systems
Relational Concept Bottleneck Models
ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
ReMAP: Neural Model Reprogramming with Network Inversion and Retrieval-Augmented Mapping for Adaptive Motion Forecasting
ReMoDetect: Reward Models Recognize Aligned LLM's Generations
Replicable Uniformity Testing
Representation noising effectively prevents harmful fine-tuning on LLMs
Reproducibility Study Of Learning Fair Graph Representations Via Automated Data Augmentations
Reproducibility Study of "Learning Perturbations to Explain Time Series Predictions"
Repurposing Language Models into Embedding Models: Finding the Compute-Optimal Recipe
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
Rethinking Memory and Communication Costs for Efficient Large Language Model Training
Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz
Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis
Retrieval & Fine-Tuning for In-Context Tabular Models
RETR: Multi-View Radar Detection Transformer for Indoor Perception
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference
Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
Revisiting Differentially Private ReLU Regression
Revisiting motion information for RGB-Event tracking with MOT philosophy
RMLR: Extending Multinomial Logistic Regression into General Geometries
Robust and Faster Zeroth-order Minimax Optimization: Complexity and Applications
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
Robust Sparse Regression with Non-Isotropic Designs
Rough Transformers: Lightweight Continuous-Time Sequence Modelling with Path Signatures
Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport
Safe Exploitative Play in Stochastic Bayesian Games with Untrusted Type Beliefs
SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained Models
Safety through feedback in Constrained RL
Samba: Severity-aware Recurrent Modeling for Cross-domain Medical Image Grading
SAMPa: Sharpness-aware Minimization Parallelized
SampDetox: Black-box Backdoor Defense via Perturbation-based Sample Detoxification
Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut
Sample-Efficient Constrained Reinforcement Learning with General Parameterization
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Scalable Constrained Policy Optimization for Safe Multi-agent Reinforcement Learning
Scalable DP-SGD: Shuffling vs. Poisson Subsampling
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation
Score-Optimal Diffusion Schedules
SCOREQ: Speech Quality Assessment with Contrastive Regression
SCRREAM : SCan, Register, REnder And Map: A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark
Second-order forward-mode optimization of recurrent neural networks for neuroscience
Seeing is NOT Always Believing! Unveiling the True Symmetric Moral Consistency of Large Language Models
Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment
SegVol: Universal and Interactive Volumetric Medical Image Segmentation
Selective Attention: Enhancing Transformer through Principled Context Control
Self-Calibrating Conformal Prediction
SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures
Self-Guided Masked Autoencoder
Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments
Semantic Feature Learning for Universal Unsupervised Cross-Domain Retrieval
Semi-Discrete Optimal Transport: Nearly Minimax Estimation With Stochastic Gradient Descent and Adaptive Entropic Regularization
Semi-supervised Knowledge Transfer Across Multi-omic Single-cell Data
Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity
Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks
Set-based Neural Network Encoding Without Weight Tying
SGLang: Efficient Execution of Structured Language Model Programs
Shape analysis for time series
Should We Really Edit Language Models? On the Evaluation of Edited Language Models
SimGen: Simulator-conditioned Driving Scene Generation
Simplifying Constraint Inference with Inverse Reinforcement Learning
Skill-aware Mutual Information Optimisation for Zero-shot Generalisation in Reinforcement Learning
Slight Corruption in Pre-training Data Makes Better Diffusion Models
SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM
SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction
Sm: enhanced localization in Multiple Instance Learning for medical imaging classification
Smoothie: Label Free Language Model Routing
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space
SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
SOI: Scaling Down Computational Complexity by Estimating Partial States of the Model
SongCreator: Lyrics-based Universal Song Generation
Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras
Speaking Your Language: Spatial Relationships in Interpretable Emergent Communication
SPEAR: Exact Gradient Inversion of Batches in Federated Learning
Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting
SpeedLoader: An I/O efficient scheme for heterogeneous and distributed LLM operation
Spiking Graph Neural Network on Riemannian Manifolds
SSDM: Scalable Speech Dysfluency Modeling
Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning
State Chrono Representation for Enhancing Generalization in Reinforcement Learning
Stealth edits to large language models
Steganalysis on Digital Watermarking: Is Your Robustness a Maginot Line?
Stepping Forward on the Last Mile
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
STONE: A Submodular Optimization Framework for Active 3D Object Detection
Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning
Stylus: Automatic Adapter Selection for Diffusion Models
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagery
Synthetic Programming Elicitation and Repair for Text-to-Code in Very Low-Resource Programming Languages
TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases
Talking Heads: Understanding Inter-Layer Communication in Transformer Language Models
Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting
TARSS-Net: Temporal-Aware Radar Semantic Segmentation Network
Team-Fictitious Play for Reaching Team-Nash Equilibrium in Multi-team Games
Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesis
Temporal-Difference Learning Using Distributed Error Signals
Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed
Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor
Testing Calibration in Nearly-Linear Time
Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment
Test-Time Debiasing of Vision-Language Embeddings
Text-Aware Diffusion for Policy Learning
TextCtrl: Diffusion-based Scene Text Editing with Prior Guidance Control
Text-Guided Image Editing in Around 7 Steps with Invertible Consistency Distillation
Text-Infused Attention and Foreground-Aware Modeling for Zero-Shot Temporal Action Detection
The Expressive Capacity of State Space Models: A Formal Language Perspective
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
The GAN is dead; long live the GAN! A Modern GAN Baseline
The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations
The Power of Hard Attention Transformers on Data Sequences: A formal language theoretic perspective
The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
The Secretary Problem with Predicted Additive Gap
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better
TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices
Topic-Conversation Relevance (TCR) Dataset and Benchmarks
Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models
Toward Reliable, Reproducible, and Practical Human Evaluation Protocol for Text-to-Video Models
Toward Semantic Gaze Target Detection
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
Towards Neuron Attributions in Multi-Modal Large Language Models
Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework
Towards training digitally-tied analog blocks via hybrid gradient computation
Towards Unsupervised Model Selection for Domain Adaptive Object Detection
Towards Visual Text Design Transfer Across Languages
Toxicity Detection for Free
Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network
Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning
Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts
Training LLMs to Better Self-Debug and Explain Code
Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear $q^\pi$-Realizability and Concentrability
Transcoders find interpretable LLM feature circuits
Transductive Sample Complexities Are Compact
Transferable Reinforcement Learning via Generalized Occupancy Models
Transfer Learning for Diffusion Models
Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization
Transformer Doctor: Diagnosing and Treating Vision Transformers
Transformers need glasses! Information over-squashing in language tasks
Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learner
UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training
Ultrafast classical phylogenetic method beats large protein language models on variant effect prediction
UltraMedical: Building Specialized Generalists in Biomedicine
Understanding Information Storage and Transfer in Multi-Modal Large Language Models
Understanding Multi-Granularity for Open-Vocabulary Part Segmentation
Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective
Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs
Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning
UniMTS: Unified Pre-training for Motion Time Series
Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image
Universality in Transfer Learning for Linear Models
Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
Universal Online Convex Optimization with $1$ Projection per Round
Universal Sample Coding
Unleash Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback
Unraveling Molecular Structure: A Multimodal Spectroscopic Dataset for Chemistry
Unscrambling disease progression at scale: fast inference of event permutations with optimal transport
UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation
Unsupervised Hierarchy-Agnostic Segmentation: Parsing Semantic Image Structure
Unsupervised Object Detection with Theoretical Guarantees
Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
UPS: Unified Projection Sharing for Lightweight Single-Image Super-resolution and Beyond
UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction
Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
Value Imprint: A Technique for Auditing the Human Values Embedded in RLHF Datasets
Vector Quantization Prompting for Continual Learning
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
Virtual Scanning: Unsupervised Non-line-of-sight Imaging from Irregularly Undersampled Transients
VisMin: Visual Minimal-Change Understanding
Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
Vivid-ZOO: Multi-View Video Generation with Diffusion Model
VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark
VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images
Vript: A Video Is Worth Thousands of Words
VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
Wasserstein convergence of Cech persistence diagrams for samplings of submanifolds
Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness
WATT: Weight Average Test Time Adaptation of CLIP
What does guidance do? A fine-grained analysis in a simple setting
When is Multicalibration Post-Processing Necessary?
When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search
WhodunitBench: Evaluating Large Multimodal Agents via Murder Mystery Games
Who Needs Features? On the Surprising Effectiveness of Attention Transfer for Vision Transformers
Who’s asking? User personas and the mechanics of latent misalignment
Who’s Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation
WikiDO: Evaluating Out-of-Distribution Generalization of Vision-Language Models in Cross-Modal Retrieval
WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs
WizardArena: Post-training Large Language Models via Simulated Offline Chatbot Arena
Would I Lie To You? Inference Time Alignment of Language Models using Direct Preference Heads
xLSTM: Extended Long Short-Term Memory
YOLOv10: Real-Time End-to-End Object Detection
Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training
Zero-Shot Scene Reconstruction from Single Images with Deep Prior Assembly
Zero-Shot Tokenizer Transfer
Zipfian Whitening
(ends 7:30 PM)
Creative AI Session 6 [4:30-4:33]
(ends 4:33 PM)
Break:
Coffee Break
(ends 5:30 PM)
7:30 p.m.
Bridging the Future [7:30-9:30]
(ends 9:30 PM)

FRI 13 DEC
7:30 a.m.
Registration (East & West)
(ends 6:00 PM)
Break:
Coffee Break
(ends 8:30 AM)
8:30 a.m.
Invited Talk:
Getting robots to learn how to interact with the world
Danica Kragic
(ends 9:30 AM)
9:30 a.m.
Break:
Coffee Break
(ends 10:00 AM)
10 a.m.
Oral Session 5A [10:00-11:00]
Learning rigid-body simulators over implicit shapes for large-scale scenes and vision
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning
Scale Equivariant Graph Meta Networks
(ends 11:00 AM)
Oral Session 5B [10:00-11:00]
Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering
Do Finetti: On Causal Effects for Exchangeable Data
Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments
(ends 11:00 AM)
Oral Session 5C [10:00-11:00]
Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery
Convolutional Differentiable Logic Gate Networks
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
(ends 11:00 AM)
Oral Session 5D [10:00-11:00]
Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning Framework
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Learning Formal Mathematics From Intrinsic Motivation
(ends 11:00 AM)
11 a.m.
Poster Session 5 [11:00-2:00]
Posters 11:00-2:00
Activating Self-Attention for Multi-Scene Absolute Pose Regression
Adversarial Generation of Hierarchical Gaussians for 3D Generative Model
Almost Surely Asymptotically Constant Graph Neural Networks
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities
CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
Combining Observational Data and Language for Species Range Estimation
DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction
Dynamic Service Fee Pricing under Strategic Behavior: Actions as Instruments and Phase Transition
Finding Transformer Circuits With Edge Pruning
Hardness of Learning Neural Networks under the Manifold Hypothesis
Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random
Long-tailed Object Detection Pretraining: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
MedCalc-Bench: Evaluating Large Language Models for Medical Calculations
MeLLoC: Lossless Compression with High-order Mechanism Learning
NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes
Optimal Algorithms for Learning Partitions with Faulty Oracles
Polyhedral Complex Derivation from Piecewise Trilinear Networks
Provable Editing of Deep Neural Networks using Parametric Linear Relaxation
Quality-Improved and Property-Preserved Polarimetric Imaging via Complementarily Fusing
Quantitative Convergences of Lie Group Momentum Optimizers
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models
Robust Offline Active Learning on Graphs
Safe LoRA: The Silver Lining of Reducing Safety Risks when Finetuning Large Language Models
SETBENCH: Assessing the Analytical and Semantic Robustness of Language Models
SnapKV: LLM Knows What You are Looking for Before Generation
Solving Inverse Problems via Diffusion Optimal Control
Symbolic Regression with a Learned Concept Library
TabEBM: A Tabular Data Augmentation Method with Class-Specific Energy-Based Models
Testably Learning Polynomial Threshold Functions
The iNaturalist Sounds Dataset
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
$M^3$GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and Generation
$\text{Di}^2\text{Pose}$: Discrete Diffusion Model for Occluded 3D Human Pose Estimation
$\textit{Read-ME}$: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
$\texttt{dopanim}$: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans
2D-OOB: Attributing Data Contribution through Joint Valuation Framework
4-bit Shampoo for Memory-Efficient Network Training
A Bayesian Approach to Data Point Selection
Accelerating Self-supervised Learning Pretraining
ACFun: Abstract-Concrete Fusion Facial Stylization
Achievable distributional robustness when the robust risk is only partially identified
A Critical Evaluation of AI Feedback for Aligning Large Language Models
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
Action Imitation in Common Action Space for Customized Action Image Synthesis
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
Active Perception for Grasp Detection via Neural Graspness Field
Active preference learning for ordering items in- and out-of-sample
Active Set Ordering
Adaptive $Q$-Aid for Conditional Supervised Learning in Offline Reinforcement Learning
Adaptive Domain Learning for Cross-domain Image Denoising
Adaptive Image Quality Assessment via Teaching Large Multimodal Models to Compare
Adaptive Labeling for Efficient Out-of-distribution Model Evaluation
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters
Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning
Adversarial Moment-Matching Distillation of Large Language Models
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Need
A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
A generalized neural tangent kernel for surrogate gradient learning
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP
A hierarchical decomposition for explaining ML performance discrepancies
AID: Attention Interpolation of Text-to-Image Diffusion
Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists
ALI-Agent: Assessing LLMs' Alignment with Human Values via Agent-based Evaluation
Aligning Model Properties via Conformal Risk Control
Aligning Vision Models with Human Aesthetics in Retrieval: Benchmarks and Algorithms
Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation
Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits
Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos
Amortized Bayesian Experimental Design for Decision-Making
An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization
ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models
Analysing CLIP's Zero-Shot Image Classification via Mutual Knowledge
Analysis of Corrected Graph Convolutions
An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning
An engine not a camera: Measuring performative power of online search
A New Neural Kernel Regime: The Inductive Bias of Multi-Task Training
An exactly solvable model for emergence and scaling laws
An eye for an ear: zero-shot audio description leveraging an image captioner with audio-visual token distribution matching
An Image is Worth 32 Tokens for Reconstruction and Generation
A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
A Prompt Learning based Regulation Framework for Generalizable Point Cloud Analysis
Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting
Are Large Language Models Good Statisticians?
A Robust Mixed-Effects Bandit Algorithm for Assessing Mobile Health Interventions
A Simple yet Universal Framework for Depth Completion
A structure-aware framework for learning device placements on computation graphs
Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families
A Theoretical Understanding of Self-Correction through In-context Alignment
AttnDreamBooth: Towards Text-Aligned Personalized Text-to-Image Generation
AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation
AudioMarkBench: Benchmarking Robustness of Audio Watermarking
Auditing Local Explanations is Hard
Autonomous Agent for Collaborative Task under Information Asymmetry
Avoiding Undesired Future with Minimal Cost in Non-Stationary Environments
Bandits with Preference Feedback: A Stackelberg Game Perspective
Bayesian Optimization of Functions over Node Subsets in Graphs
BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
Benchmarking Trustworthiness of Multimodal Large Language Models: A Comprehensive Study
BertaQA: How Much Do Language Models Know About Local Culture?
Beyond Aesthetics: Cultural Competence in Text-to-Image Models
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization
Beyond Prompts: Dynamic Conversational Benchmarking of Large Language Models
Bias Amplification in Language Model Evolution: An Iterated Learning Perspective
Bias Detection via Signaling
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding
Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control
Binarized Diffusion Model for Image Super-Resolution
BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity
BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval
BLURD: Benchmarking and Learning using a Unified Rendering and Diffusion Model
BMRS: Bayesian Model Reduction for Structured Pruning
Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
Boundary Matters: A Bi-Level Active Finetuning Method
Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension
BrainBits: How Much of the Brain are Generative Reconstruction Methods Using?
Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers
Bridging semantics and pragmatics in information-theoretic emergent communication
Building a stable classifier with the inflated argmax
Building Network Architectures for Continual Reinforcement Learning with Parseval Regularization
Building Timeseries Dataset: Empowering Large-Scale Building Analytics
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Can an AI Agent Safely Run a Government? Existence of Probably Approximately Aligned Policies
Can We Leave Deepfake Data Behind in Training Deepfake Detector?
CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes
CA-SSLR: Condition-Aware Self-Supervised Learning Representation for Generalized Speech Processing
Causal Effect Identification in a Sub-Population with Latent Variables
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory
Chain of Thoughtlessness? An Analysis of CoT in Planning
CiteME: Can Language Models Accurately Cite Scientific Claims?
CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models
Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations
Classification Done Right for Vision-Language Pre-Training
ClavaDDPM: Multi-relational Data Synthesis with Cluster-guided Diffusion Models
ClevrSkills: Compositional Language And Visual Understanding in Robotics
Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation
Clustering in Causal Attention Masking
Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers
Coded Computing: A Learning-Theoretic Framework
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
CoIN: A Benchmark of Continual Instruction Tuning for Multimodel Large Language Models
ColJailBreak: Collaborative Generation and Editing for Jailbreaking Text-to-Image Deep Generation
Collaborative Refining for Learning from Inaccurate Labels
CoLLaM: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models
CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding
Compact Language Models via Pruning and Knowledge Distillation
Compositional Estimation of Lipschitz Constants for Deep Neural Networks
Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models
Conditional Outcome Equivalence: A Quantile Alternative to CATE
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs
ConStat: Performance-Based Contamination Detection in Large Language Models
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model
ContactField: Implicit Field Representation for Multi-Person Interaction Geometry
Context and Geometry Aware Voxel Transformer for Semantic Scene Completion
ContextGS : Compact 3D Gaussian Splatting with Anchor Level Context Model
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
Continuous Partitioning for Graph-Based Semi-Supervised Learning
Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation
Contrastive dimension reduction: when and how?
Convergence of $\log(1/\epsilon)$ for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis
Convolutional Differentiable Logic Gate Networks
Copycats: the many lives of a publicly available medical imaging dataset
CoVoMix: Advancing Zero-Shot Speech Generation for Human-like Multi-talker Conversations
Critically Assessing the State of the Art in Neural Network Verification
Cronos: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks
Cross-modal Representation Flattening for Multi-modal Domain Generalization
CultureLLM: Incorporating Cultural Differences into Large Language Models
Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning
Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction
DAGER: Exact Gradient Inversion for Large Language Models
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
Data Attribution for Text-to-Image Models by Unlearning Synthesized Images
Data-faithful Feature Attribution: Mitigating Unobservable Confounders via Instrumental Variables
Data Selection for Task-Specific Model Finetuning
Debiasing Synthetic Data Generated by Deep Generative Models
Deep Bayesian Active Learning for Preference Modeling in Large Language Models
Deep Graph Mating
Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module
Deep linear networks for regression are implicitly regularized towards flat minima
Deep Policy Gradient Without Batch Updates or a Replay Buffer
Deep Support Vectors
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
DeiSAM: Segment Anything with Deictic Prompting
Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems
Detecting and Measuring Confounding Using Causal Mechanism Shifts
DF40: Toward Next-Generation Deepfake Detection
DiffAug: A Diffuse-and-Denoise Augmentation for Training Robust Classifiers
Differentially Private Equivalence Testing for Continuous Distributions and Application
DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data
DiffTOP: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation Learning
Diffusion for World Modeling: Visual Details Matter in Atari
Diffusion Policies creating a Trust Region for Offline Reinforcement Learning
Diffusion Priors for Variational Image Denoising
Diffusion Representation for Reinforcement Learning
Diffusion Twigs with Loop Guidance for Conditional Graph Generation
DI-MaskDINO: A Joint Object Detection and Instance Segmentation Model
Direct Consistency Optimization for Robust Customization of Text-to-Image Diffusion models
Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandits
Discrete Flow Matching
DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis
Disentangled Representation Learning in Non-Markovian Causal Systems
Dissecting Query-Key Interaction in Vision Transformers
Distilling Costly Set Functions to Parametric Families
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm
Distribution-Aware Data Expansion with Diffusion Models
Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec
DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors
DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models
DN-4DGS: Denoised Deformable Network with Temporal-Spatial Aggregation for Dynamic Scene Rendering
Does Video-Text Pretraining Help Open-Vocabulary Online Action Detection?
Do Finetti: On Causal Effects for Exchangeable Data
Do LLMs Build World Representations? Probing Through the Lens of State Abstraction
Domain Adaptation for Large-Vocabulary Object Detectors
Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences
Don't Look Twice: Faster Video Transformers with Run-Length Tokenization
DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction
Do's and Don'ts: Learning Desirable Skills with Instruction Videos
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation
DrivAerNet++: A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
Du-IN: Discrete units-guided mask modeling for decoding speech from Intracranial Neural signals
Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron
Dynamic Subgroup Identification in Covariate-adjusted Response-adaptive Randomization Experiments
DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation
Effective Exploration Based on the Structural Information Principles
Efficiency for Free: Ideal Data Are Transportable Representations
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
Efficient Algorithm and Improved Regret for RL with Multinomial Logit Function Approximation
Efficient Attention using Low-Dimensional Keys
Efficient LLM Scheduling by Learning to Rank
Efficient multi-prompt evaluation of LLMs
Efficient Prompt Optimization Through the Lens of Best Arm Identification
Embedding Dimension of Contrastive Learning and $k$-Nearest Neighbors
ENAT: Rethinking Spatial-temporal Interactions in Token-based Image Synthesis
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
Enhancing Large Vision Language Models with Self-Training on Image Comprehension
Enhancing Motion in Text-to-Video Generation with Decomposed Encoding and Conditioning
Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning
Enhancing vision-language models for medical imaging: bridging the 3D gap with innovative slice selection
Ensuring Right Prediction With Right Rationale
EpiCare: A Reinforcement Learning Benchmark for Dynamic Treatment Regimes
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data
Evaluate calibration of language models with folktexts
Evaluation of Text-to-Video Generation Models: A Dynamics Perspective
Everyday Object Meets Vision-and-Language Navigation Agent via Backdoor
Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking
Exclusively Penalized Q-learning for Offline Reinforcement Learning
Exogenous Matching: Learning Good Proposals for Tractable Counterfactual Estimation
Expected Probabilistic Hierarchies
Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering
Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration
Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment
Exploring Context Window of Large Language Models via Decomposed Positional Vectors
Exploring Fixed Point in Image Editing: Theoretical Support and Convergence Optimization
Exploring the Role of Large Language Models in Prompt Encoding for Diffusion Models
Exploring Token Pruning in Vision State Space Models
Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium
Fair Online Bilateral Trade
FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation
Faster Repeated Evasion Attacks in Tree Ensembles
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
FedAvP: Augment Local Data via Shared Policy in Federated Learning
Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning
Feedback control guides credit assignment in biological circuits
FINALLY: fast and universal speech enhancement with studio-like quality
FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making
Fine-grained Analysis of In-context Linear Estimation
Fisher Flow Matching for Discrete Data
Fixed Confidence Best Arm Identification in the Bayesian Setting
Flex-MoE: Addressing Missing Modalities in Alzheimer’s Disease with Flexible Mixture-of-Experts
Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery
Flipping-based Policy for Chance-Constrained Markov Decision Processes
Flow Snapshot Neurons in Action: Deep Neural Networks Generalize to Biological Motion Perception
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
fMRI predictors based on language models of increasing complexity recover brain left lateralization
FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding
From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection
From Similarity to Superiority: Channel Clustering for Time Series Forecasting
Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models
Frustratingly Easy Test-Time Adaptation of Vision-Language Models
FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event Detection
Fully Explicit Dynamic Gaussian Splatting
FUSE: Fast Unified Simulation and Estimation for PDEs
FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving
G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training
GarmentLab: A Unified Simulation and Benchmark for Garment Manipulation
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
GenAI Arena: An Open Evaluation Platform for Generative Models
Gene-Gene Relationship Modeling Based on Genetic Evidence for Single-Cell RNA-Seq Data Imputation
General Detection-based Text Line Recognition
Generalizable Implicit Motion Modeling for Video Frame Interpolation
Generalization Analysis for Label-Specific Representation Learning
Generalized Linear Bandits with Limited Adaptivity
Generalizing CNNs to graphs with learnable neighborhood quantization
GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts
Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning Framework
GL-NeRF: Gauss-Laguerre Quadrature Enables Training-Free NeRF Acceleration
Global Convergence in Training Large-Scale Transformers
Globally Convergent Variational Inference
Goal-Conditioned On-Policy Reinforcement Learning
GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching
Gradient-based Discrete Sampling with Automatic Cyclical Scheduling
Gradient-free Decoder Inversion in Latent Diffusion Models
Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts
GraphMorph: Tubular Structure Extraction by Morphing Predicted Graphs
Graph Neural Networks Need Cluster-Normalize-Activate Modules
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models
Grid4D: 4D Decomposed Hash Encoding for High-fidelity Dynamic Scene Rendering
GrootVL: Tree Topology is All You Need in State Space Model
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model
Grounding Multimodal Large Language Models in Actions
Group Robust Preference Optimization in Reward-free RLHF
GTA: A Benchmark for General Tool Agents
GuardT2I: Defending Text-to-Image Models from Adversarial Prompts
Harnessing small projectors and multiple views for efficient vision pretraining
HEMM: Holistic Evaluation of Multimodal Foundation Models
Hierarchical Programmatic Option Framework for Solving Long and Repetitive Tasks
High-probability complexity bounds for stochastic non-convex minimax optimization
How Diffusion Models Learn to Factorize and Compose
How does PDE order affect the convergence of PINNs?
How Does Variance Shape the Regret in Contextual Bandits?
How many classifiers do we need?
How to Scale Inverse RL to Large State Spaces? A Provably Efficient Approach
HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors
Hybrid Generative AI for De Novo Design of Co-Crystals with Enhanced Tabletability
Hybrid Mamba for Few-Shot Segmentation
HyperLogic: Enhancing Diversity and Accuracy in Rule Learning with HyperNets
I2EBench: A Comprehensive Benchmark for Instruction-based Image Editing
IaC-Eval: A code generation benchmark for Infrastructure-as-Code programs
Identifiability Analysis of Linear ODE Systems with Hidden Confounders
Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments
Identifying Selections for Unsupervised Subtask Discovery
If You Want to Be Robust, Be Wary of Initialization
IllumiNeRF: 3D Relighting without Inverse Rendering
Image2Struct: A Benchmark for Evaluating Vision-Language Models in Extracting Structured Information from Images
Image-aware Evaluation of Generated Medical Reports
Images that Sound: Composing Images and Sounds on a Single Canvas
IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation
ImOV3D: Learning Open Vocabulary Point Clouds 3D Object Detection from Only 2D Images
Implicit Optimization Bias of Next-token Prediction in Linear Models
Implicit regularization of multi-task learning and finetuning: multiple regimes of feature reuse
Improved Sample Complexity for Multiclass PAC Learning
Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
Improving self-training under distribution shifts via anchored confidence with theoretical guarantees
Improving Subgroup Robustness via Data Selection
Improving Temporal Link Prediction via Temporal Walk Matrix Projection
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies
Incentivizing Quality Text Generation via Statistical Contracts
In-Context Learning State Vector with Inner and Momentum Optimization
In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness
IndicVoices-R: Unlocking a Massive Multilingual Multi-speaker Speech Corpus for Scaling Indian TTS
Indoor Air Quality Dataset with Activities of Daily Living in Low to Middle-income Communities
Inferring Neural Signed Distance Functions by Overfitting on Single Noisy Point Clouds through Finetuning Data-Driven based Priors
InfiBench: Evaluating the Question-Answering Capabilities of Code Large Language Models
Infinite Limits of Multi-head Transformer Dynamics
INQUIRE: A Natural World Text-to-Image Retrieval Benchmark
InstructG2I: Synthesizing Images from Multimodal Attributed Graphs
Instruction Embedding: Latent Representations of Instructions Towards Task Identification
Interactive Deep Clustering via Value Mining
InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques
Interpreting Learned Feedback Patterns in Large Language Models
Interpreting the Weight Space of Customized Diffusion Models
Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning
Invisible Image Watermarks Are Provably Removable Using Generative AI
IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons
Is Function Similarity Over-Engineered? Building a Benchmark
Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?
Is Multiple Object Tracking a Matter of Specialization?
Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models.
Is Your HD Map Constructor Reliable under Sensor Corruptions?
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling
Kermut: Composite kernel regression for protein variant effects
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
Key-Grid: Unsupervised 3D Keypoints Detection using Grid Heatmap Features
kGym: A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution
KOALA: Empirical Lessons Toward Memory-Efficient and Fast Diffusion Models for Text-to-Image Synthesis
Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference
Label Delay in Online Continual Learning
Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models
Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation
Large Scene Model: Real-time Unposed Images to Semantic 3D
Latent functional maps
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure
Learning Elastic Costs to Shape Monge Displacements
Learning Formal Mathematics From Intrinsic Motivation
Learning Frequency-aware Vision Foundation Model for Domain Generalized Semantic Segmentation
Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks
Learning from Highly Sparse Spatio-temporal Data
Learning rigid-body simulators over implicit shapes for large-scale scenes and vision
Learning Superconductivity from Ordered and Disordered Material Structures
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games
Learning the Optimal Policy for Balancing Multiple Short-Term and Long-Term Rewards
Learning to compute Gröbner bases
Learning to Shape In-distribution Feature Space for Out-of-distribution Detection
Learning to Understand: Identifying Interactions via the Möbius Transform
Learning Truncated Causal History Model for Video Restoration
Learning via Surrogate PAC-Bayes
Learning with Fitzpatrick Losses
Learn more, but bother less: parameter efficient continual learning
Leveraging Environment Interaction for Automated PDDL Generation and Planning with Large Language Models
Leveraging Separated World Model for Exploration in Visually Distracted Environments
Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images
LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication
LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS
Linear Causal Bandits: Unknown Graph and Soft Interventions
Listenable Maps for Zero-Shot Audio Classifiers
Localized Zeroth-Order Prompt Optimization
Local to Global: Learning Dynamics and Effect of Initialization for Transformers
Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild
Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli
Long-range Meta-path Search on Large-scale Heterogeneous Graphs
Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering
LotCLIP: Improving Language-Image Pre-training for Long Text Understanding
Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materials
Make Your LLM Fully Utilize the Context
MambaSCI: Efficient Mamba-UNet for Quad-Bayer Patterned Video Snapshot Compressive Imaging
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models
MatrixNet: Learning over symmetry groups using learned group representations
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance
Measuring Per-Unit Interpretability at Scale Without Humans
MECD: Unlocking Multi-Event Causal Discovery in Video Reasoning
Mechanism Design Through Exploration Control: Optimizing the Trade-Off Between User and Creator Engagement
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Membership Inference Attacks against Large Language Models via Self-prompt Calibration
MergeMinds: Boosting Multilingual Reasoning with the Built-in Capabilities of LLMs
Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
Metric from Human: Zero-shot Monocular Metric Depth Estimation via Test-time Adaptation
Mind the Graph When Balancing Data for Fairness or Robustness
Minimum Entropy Coupling with Bottleneck
Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration
MKGL: Mastery of a Three-Word Language
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
MoGU: A Framework for Enhancing Safety of Open-Sourced LLMs While Preserving Their Usability
Molecule Design by Latent Prompt Transformer
Most Influential Subset Selection: Challenges, Promises, and Beyond
Multi-Label Learning with Stronger Consistency Guarantees
Multi-Label Open Set Recognition
Multi-modal Situated Reasoning in 3D Scenes
MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities
Multi-Task Prompt Decision Transformer for Efficient Unseen Task Generalization
Multivariate Probabilistic Time Series Forecasting with Correlated Errors
Multiview Scene Graph
Mutual Information Estimation via $f$-Divergence and Data Derangements
MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing
MVSplat360: Benchmarking 360$\textdegree$ Generalizable 3D Novel View Synthesis from Sparse Views
N-agent Ad Hoc Teamwork
Nature-Inspired Local Propagation
Navigating the Effect of Parametrization for Dimensionality Reduction
Nearly Minimax Optimal Submodular Maximization with Bandit Feedback
NeuMA: Neural Material Adaptor for Visual Grounding of Intrinsic Dynamics
NeuralClothSim: Neural Deformation Fields Meet the Thin Shell Theory
Neural Conditional Probability for Inference
Neural decoding from stereotactic EEG: accounting for electrode variability across subjects
Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit
Neural networks with fast and bounded units learn flexible task abstractions
Neural Persistence Dynamics
NeuralThink: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
Newswire: A Large-Scale Structured Database of a Century of Historical News
Newton Informed Neural Operator for Computing Multiple Solutions of Nonlinear Partials Differential Equations
Nimbus: Secure and Efficient Two-Party Inference for Transformers
Noether's Razor: Learning Conserved Quantities
Noise Contrastive Alignment of Language Models with Explicit Rewards
NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
Non-convolutional graph neural networks.
Nonparametric Evaluation of Noisy ICA Solutions
Object segmentation from common fate: Motion energy processing enables human-like zero-shot generalization to random dot stimuli
Observational Scaling Laws and the Predictability of Langauge Model Performance
OccFusion: Rendering Occluded Humans with Generative Diffusion Priors
Octopus: A Multi-modal LLM with Parallel Recognition and Sequential Understanding
ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings
OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation
On Causal Discovery in the Presence of Deterministic Relations
On Differentially Private Subspace Estimation in a Distribution-Free Setting
On Feature Learning in Structured State Space Models
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
On Learning Physical Neural Representations of Dynamical Data
Online Consistency of the Nearest Neighbor Rule
Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
Online Iterative Reinforcement Learning from Human Feedback with General Preference Model
Online Learning with Sublinear Best-Action Queries
OnlineTAS: An Online Baseline for Temporal Action Segmentation
On Sampling Strategies for Spectral Model Sharding
On the Ability of Developers' Training Data Preservation of Learnware
On the Adversarial Robustness of Benjamini Hochberg
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
On the Efficiency of ERM in Feature Learning
On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks
On the Limitations of Fractal Dimension as a Measure of Generalization
On the Noise Robustness of In-Context Learning for Text Generation
On the Scalability of GNNs for Molecular Graphs
On the Worst Prompt Performance of Large Language Models
OpenDlign: Enhancing Open-World 3D Learning with Depth-Aligned Images
OpenSatMap: A Fine-grained High-resolution Satellite Dataset for Large-scale Map Construction
OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators
OPS: Occupancy Prediction as A Sparse Set
Optical Diffusion Models for Image Generation
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
Optimal Flow Matching: Learning Straight Trajectories in Just One Step
Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos
Optimization Algorithm Design via Electric Circuits
Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits
Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks
OVT-B: A New Large-Scale Benchmark for Open-Vocabulary Multi-Object Tracking
PACE: marrying the generalization of PArameter-efficient fine-tuning with Consistency rEgularization
Pandora's Box: Towards Building Universal Attackers against Real-World Large Vision-Language Models
Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning
Parametric model reduction of mean-field and stochastic systems via higher-order action matching
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics
Particle Semi-Implicit Variational Inference
Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications
Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models
Phased Consistency Model
PhyRecon: Physically Plausible Neural Scene Reconstruction
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
Post-Hoc Reversal: Are We Selecting Models Prematurely?
Predictive Attractor Models
Pricing and Competition for Generative AI
Private and Personalized Frequency Estimation in a Federated Setting
Private Attribute Inference from Images with Vision-Language Models
Private Geometric Median
Private Online Learning via Lazy Algorithms
PrivAuditor: Benchmarking Data Protection Vulnerabilities in LLM Adaptation Techniques
PrivCirNet: Efficient Private Inference via Block Circulant Transformation
ProgressGym: Alignment with a Millennium of Moral Progress
Prompting LLMs for Social Relation Reasoning via Greedy Segment Optimization
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
Proportional Fairness in Clustering: A Social Choice Perspective
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
Pruning neural network models for gene regulatory dynamics using data and domain knowledge
Pseudo-Siamese Directional Transformers for Self-Supervised Real-World Denoising
PTQ4DiT: Post-training Quantization for Diffusion Transformers
PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics
PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition
QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Quantum Algorithms for Non-smooth Non-convex Optimization
Query-Based Adversarial Prompt Generation
Query-Efficient Correlation Clustering with Noisy Oracle
QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees
RClicks: Realistic Click Simulation for Benchmarking Interactive Segmentation
Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices
Recovering Complete Actions for Cross-dataset Skeleton Action Recognition
RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance
[Re] CUDA: Curriculum of Data Augmentation for Long‐tailed Recognition
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models
ReFT: Representation Finetuning for Language Models
Regularized Q-Learning
Reinforcement Learning-Guided Semi-Supervised Learning
ReLU Characteristic Activation Analysis
ReMI: A Dataset for Reasoning with Multiple Images
Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma
Resolving Discrepancies in Compute-Optimal Scaling of Language Models
ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search
Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus
Rethinking the Dynamics of Spiking Neural Networks
Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective
Retrieval-Augumented Diffusion Models for Time Series Forecasting
Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos
Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective
Revisiting the Integration of Convolution and Attention for Vision Backbone
Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy
RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation
RobIR: Robust Inverse Rendering for High-Illumination Scenes
Robust Gaussian Processes via Relevance Pursuit
Robust group and simultaneous inferences for high-dimensional single index model
Robust Reinforcement Learning from Corrupted Human Feedback
Robust Reinforcement Learning with General Utility
S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models
Sample Complexity Reduction through Policy Difference Estimation in RL
Sample-efficient Bayesian Optimisation Using Known Invariances
Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
Scalable and Stable Parallelization of Nonlinear RNNs
Scalable Kernel Inverse Optimization
Scale Equivariant Graph Meta Networks
Scale-invariant Optimal Sampling for Rare-events Data and Sparse Models
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
Scaling Sign Language Translation
Scaling the Codebook Size of VQ-GAN to 100,000 with a Utilization Rate of 99%
SeafloorGenAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey
Search for Efficient Large Language Models
Seeing Beyond the Crop: Using Language Priors for Out-of-Bounding Box Keypoint Prediction
Self-Evolution Decoding for Improving Factuality in Large Language Models
Self-Guiding Exploration for Combinatorial Problems
Self-Retrieval: End-to-End Information Retrieval with One Large Language Model
Seshat Global History Databank Text Dataset and Benchmark of Large Language Models' History Knowledge
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
ShopBench: A Massive Multi-Task Online Shopping Benchmark for Large Language Models
Simple and Fast Distillation of Diffusion Models
Simulated Humanoid Grasping on Diverse Objects
Single-loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
SIRIUS : Contexual Sparisty with Correction for Efficient LLMs
SkiLD: Unsupervised Skill Discovery Guided by Local Dependencies
Skinned Motion Retargeting with Dense Geometric Interaction Perception
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
Slot-VLM: Object-Event Slots for Video-Language Modeling
Smoothed Energy Guidance: Guiding Diffusion Models by Attenuating Energy Curvature of Attention
SOAP: Enhancing Efficiency of generated Code via Self-Optimization
Soft ascent-descent as a stable and flexible alternative to flooding
Source Code Foundation Models are Transferable Binary Analysis Knowledge Bases
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
SparseLLM: Towards Global Pruning of Pre-trained Language Models
Sparse maximal update parameterization: A holistic approach to sparse training dynamics
Spatio-Spectral Graph Neural Networks
SpecExec: Massively Parallel Speculative Decoding For Interactive LLM Inference on Consumer Devices
Spectral Learning of Shared Dynamics Between Generalized-Linear Processes
SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation
SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness
StackEval: Benchmarking LLMs in Coding Assistance
Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training
STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics
STL: Still Tricky Logic (for System Validation, Even When Showing Your Work)
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation
Strategic Linear Contextual Bandits
StrategyLLM: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving
Streaming Bayes GFlowNets
Structured Learning of Compositional Sequential Interventions
Structured Multi-Track Accompaniment Arrangement via Style Prior Modelling
SubgDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning
SUGARCREPE++ Dataset: Vision-Language Model Sensitivity to Semantic and Lexical Alterations
SuperDeepFool: a new fast and accurate minimal adversarial attack
Swift Sampler: Efficient Learning of Sampler by 10 parameters
SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization
Symmetric Linear Bandits with Hidden Symmetry
Symmetry-Informed Governing Equation Discovery
SyncVIS: Synchronized Video Instance Segmentation
Taming Diffusion Prior for Image Super-Resolution with Domain Shift SDEs
Task-Agnostic Machine Learning-Assisted Inference
Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization
Tell What You Hear From What You See - Video to Audio Generation Through Text
Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth
Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning
TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering
The Best of Both Worlds: Toward an Honest and Helpful Large Language Model
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
The Effectiveness of Surprisingly Popular Voting with Partial Preferences
The Fairness-Quality Tradeoff in Clustering
The Fine-Grained Complexity of Gradient Computation for Training Large Language Models
The Implicit Bias of Adam on Separable Data
The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions
The Importance of Being Scalable: Efficient Architectures for Neural Network Potentials
The Intelligible and Effective Graph Neural Additive Network
The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space
The Minimax Regret of Sequential Probability Assignment, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
Theoretical Analysis of Weak-to-Strong Generalization
The Power of Extrapolation in Federated Learning
The Power of Resets in Online Reinforcement Learning
The surprising efficiency of temporal difference learning for rare event prediction
Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
Time-Constrained Robust MDPs
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
To Err like Human: Affective Bias-Inspired Measures for Visual Emotion Recognition Evaluation
Topological obstruction to the training of shallow ReLU neural networks
Toward Conditional Distribution Calibration in Survival Prediction
Toward Real Ultra Image Segmentation: Leveraging Surrounding Context to Cultivate General Segmentation Model
Towards Calibrated Robust Fine-Tuning of Vision-Language Models
Towards Editing Time Series
Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding
Towards Learning Group-Equivariant Features for Domain Adaptive 3D Detection
Towards Multi-dimensional Explanation Alignment for Medical Classification
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers
Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline
TrackIME: Enhanced Video Point Tracking via Instance Motion Estimation
Training Compute-Optimal Protein Language Models
Training-Free Visual Prompt Learning for Multimodal Large Language Models
Trajectory Flow Matching with Applications to Clinical Time Series Modelling
Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness
Transfer Learning with Informative Priors: Simple Baselines Better than Previously Reported
Transformers Can Do Arithmetic with the Right Embeddings
Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Models
Transition Constrained Bayesian Optimization via Markov Decision Processes
Trap-MID: Trapdoor-based Defense against Model Inversion Attacks
Truthfulness of Calibration Measures
TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Models
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-World Document Analysis
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
U-DiTs: Downsample Tokens in U-Shaped Diffusion Transformers
UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language Models
Unconditional stability of a recurrent neural circuit implementing divisive normalization
Uncovering the Redundancy in Graph Self-supervised Learning Models
Understanding and Improving Training-free Loss-based Diffusion Guidance
Understanding and Minimising Outlier Features in Neural Network Training
Understanding Emergent Abilities of Language Models from the Loss Perspective
Understanding the Gains from Repeated Self-Distillation
Understanding Transformers via N-Gram Statistics
Understanding Visual Feature Reliance through the Lens of Complexity
Unelicitable Backdoors via Cryptographic Transformer Circuits
UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation
Unified Guidance for Geometry-Conditioned Molecular Generation
UniIF: Unified Molecule Inverse Folding
UniTox: Leveraging LLMs to Curate a Unified Dataset of Drug-Induced Toxicity from FDA Labels
Unity by Diversity: Improved Representation Learning for Multimodal VAEs
Universal Exact Compression of Differentially Private Mechanisms
Universal Neural Functionals
Unsupervised Discovery of Formulas for Mathematical Constants
Unveiling and Mitigating Backdoor Vulnerabilities based on Unlearning Weight Changes and Backdoor Activeness
Upping the Game: How 2D U-Net Skip Connections Dominate 3D Segmentation
UQ-Guided Hyperparameter Optimization for Iterative Learners
User-Creator Feature Dynamics in Recommender Systems with Dual Influence
Using Noise to Infer Aspects of Simplicity Without Learning
UV-free Texture Generation with Denoising and Heat Diffusion
VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks
Vision-Language Models are Strong Noisy Label Detectors
Visual Decoding and Reconstruction via EEG Embeddings with Guided Diffusion
Visual Fourier Prompt Tuning
Visual Pinwheel Center Act as Geometric Saliency Detector
Vocal Call Locator Benchmark (VCL'24) for localizing rodent vocalizations from multi-channel audio
Voila-A: Aligning Vision-Language Models with User's Gaze Attention
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation
WaveAttack: Asymmetric Frequency Obfuscation-based Backdoor Attacks Against Deep Neural Networks
Web-Scale Visual Entity Recognition: An LLM-Driven Data Approach
Weight Diffusion for Future: Learn to Generalize in Non-Stationary Environments
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning
WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking
What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information
What Variables Affect Out-Of-Distribution Generalization in Pretrained Models?
When Is Inductive Inference Possible?
Where Do Large Learning Rates Lead Us?
Wide Two-Layer Networks can Learn from Adversarial Perturbations
Wild-GS: Real-Time Novel View Synthesis from Unconstrained Photo Collections
WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
(ends 2:00 PM)
1 p.m.
Break:
Lunch Break
(ends 2:30 PM)
2:30 p.m.
Invited Talk:
Invited Talk - Rosalind Picard
Rosalind Picard
(ends 3:30 PM)
3:30 p.m.
Oral Session 6A [3:30-4:30]
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
MDAgents: An Adaptive Collaboration of LLMs for Medical Decision Making
Graph Diffusion Transformer for Multi-Conditional Molecular Generation
(ends 4:30 PM)
Oral Session 6B [3:30-4:30]
Achieving Efficient Alignment through Learned Correction
Bayesian-Guided Label Mapping for Visual Reprogramming
A Taxonomy of Challenges to Curating Fair Datasets
(ends 4:30 PM)
Oral Session 6C [3:30-4:30]
MedCalc-Bench: Evaluating Large Language Models for Medical Calculations
Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
(ends 4:30 PM)
Oral Session 6D [3:30-4:30]
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices
You Only Cache Once: Decoder-Decoder Architectures for Language Models
MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map
(ends 4:30 PM)
4:30 p.m.
Poster Session 6 [4:30-7:30]
Posters 4:30-7:30
A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models
Differentially Private Reinforcement Learning with Self-Play
Partial Transportability for Domain Generalization
Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
$C^2M^3$: Cycle-Consistent Multi-Model Merging
$E^3$: Exploring Embodied Emotion Through A Large-Scale Egocentric Video Dataset
$\nabla^2$DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials
$SE(3)$ Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation
3DCoMPaT200: Language Grounded Large-Scale 3D Vision Dataset for Compositional Recognition
4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization
A Benchmark Suite for Systematically Evaluating Reasoning Shortcuts
A Best-of-both-worlds Algorithm for Bandits with Delayed Feedback with Robustness to Excessive Delays
A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization
Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values
Achievable Fairness on Your Data With Utility Guarantees
Achieving $\tilde{O}(1/\epsilon)$ Sample Complexity for Constrained Markov Decision Process
Achieving Efficient Alignment through Learned Correction
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression
A Continuous-time Stochastic Gradient Descent Method for Continuous Data
ActFusion: a Unified Diffusion Model for Action Segmentation and Anticipation
Activation Map Compression through Tensor Decomposition for Deep Learning
ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets
AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Models
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization
Adaptive Important Region Selection with Reinforced Hierarchical Search for Dense Object Detection
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data
Advection Augmented Convolutional Neural Networks
Adversarial Environment Design via Regret-Guided Diffusion Models
A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetics
A Full-duplex Speech Dialogue Scheme Based On Large Language Model
A General Protocol to Probe Large Vision Models for 3D Physical Understanding
A Generative Model of Symmetry Transformations
AgentPoison: Red-teaming LLM Agents via Memory or Knowledge Base Backdoor Poisoning
A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding
A Kernel Perspective on Distillation-based Collaborative Learning
Aligner Encoders: Self-Attention Transformers Can Be Self-Transducers
Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
Aligning Individual and Collective Objectives in Multi-Agent Cooperation
Alignment at Pre-training! Towards Native Alignment for Arabic LLMs
AlphaMath Almost Zero: Process Supervision Without Process
ALPINE: Unveiling The Planning Capability of Autoregressive Learning in Language Models
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models
AlterMOMA: Fusion Redundancy Pruning for Camera-LiDAR Fusion Models with Alternative Modality Masking
Amortized Planning with Large-Scale Transformers: A Case Study on Chess
An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise
A New Multi-Source Light Detection Benchmark and Semi-Supervised Focal Light Detection
An Information Theoretic Perspective on Conformal Prediction
A Novel Benchmark for Decision-Making in Uncertain and Competitive Games
A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation
AnyFit: Controllable Virtual Try-on for Any Combination of Attire Across Any Scenario
AP-Adapter: Improving Generalization of Automatic Prompts on Unseen Text-to-Image Diffusion Models
A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness
Approximating the Top Eigenvector in Random Order Streams
A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness
Are Language Models Actually Useful for Time Series Forecasting?
Are Multiple Instance Learning Algorithms Learnable for Instances?
Are We on the Right Way for Evaluating Large Vision-Language Models?
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
A Siamese Transformer with Hierarchical Refinement for Lane Detection
A Simple yet Scalable Granger Causal Structural Learning from Topological Event Sequences
A simplicity bias in the learning dynamics of transformers
A Taxonomy of Challenges to Curating Fair Datasets
A Theory of Optimistically Universal Online Learnability for General Concept Classes
A Topology-aware Graph Coarsening Framework for Continual Graph Learning
Attention boosted Individualized Regression
Attention Temperature Matters in ViT-Based Cross-Domain Few-Shot Learning
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
Auditing Privacy Mechanisms via Label Inference Attacks
A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records
Autoregressive Image Diffusion: Generating Image Sequence and Application in MRI
Autoregressive Policy Optimization for Constrained Allocation Tasks
AutoSurvey: Large Language Models Can Automatically Write Surveys
AV-Cloud: Spatial Audio Rendering Through Audio-Visual Cloud Splatting
A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis
A Walsh Hadamard Derived Linear Vector Symbolic Architecture
Axioms for AI Alignment from Human Feedback
BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models
Bayesian-Guided Label Mapping for Visual Reprogramming
Bayesian Strategic Classification
Benchmarking the Attribution Quality of Vision Models
Benchmark Repositories for Better Benchmarking
Beyond Accuracy: Tracking more like Human via Visual Search
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning
Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects
BiDM: Pushing the Limit of Quantization for Diffusion Models
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance
Boosting the Transferability of Adversarial Attack on Vision Transformer with Adaptive Token Tuning
Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli
Breaking Semantic Artifacts for Generalized AI-generated Image Detection
Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences
CALVIN: Improved Contextual Video Captioning via Instruction Tuning
Can LLMs Learn by Teaching? A Preliminary Study
Capturing the denoising effect of PCA via compression ratio
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
Carrot and Stick: Eliciting Comparison Data and Beyond
Cascade of phase transitions in the training of energy-based models
Chain-of-Thought Reasoning Without Prompting
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
ClashEval: Quantifying the tug-of-war between an LLM’s internal prior and external evidence
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
CoBo: Collaborative Learning via Bilevel Optimization
Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement Learning
Communication Efficient Distributed Training with Distributed Lion
CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs
Compositional 3D-aware Video Generation with LLM Director
Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond
Computational Aspects of Bayesian Persuasion under Approximate Best Response
Confidence Regulation Neurons in Language Models
Conformal Classification with Equalized Coverage for Adaptively Selected Groups
Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data
Connectivity-Driven Pseudo-Labeling Makes Stronger Cross-Domain Segmenters
Conservative Fine-Tuning of Diffusion Models from Offline Data
Consistency Models for Scalable and Fast Simulation-Based Inference
Consistency of Neural Causal Partial Identification
Contextual Active Model Selection
Contrastive losses as generalized models of global epistasis
Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound
Co-occurrence is not Factual Association in Language Models
Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging
CosAE: Learnable Fourier Series for Image Restoration
COSMIC: Compress Satellite Image Efficiently via Diffusion Compensation
Counterfactual PPO Enhanced Shared Reflector for LLM-based Multi-agent Collaboration
COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing
CRAG - Comprehensive RAG Benchmark
CRAYM: Neural Field Optimization via Camera RAY Matching
CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy
CulturePark: Boosting Cross-cultural Understanding in Large Language Models
CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts
CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence
Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns
CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos
DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices
DARNet: Dual Attention Refinement Network with Spatiotemporal Construction for Auditory Attention Detection
DataComp-LM: In search of the next generation of training sets for language models
Data Distribution Valuation
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine Domain
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos
Decomposable Transformer Point Processes
Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.
Deep Learning for Computing Convergence Rates of Markov Chains
Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models
DeMo: Decoupling Motion Forecasting into Directional Intentions and Dynamic States
DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception
DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning
DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning
DeTrack: In-model Latent Denoising Learning for Visual Object Tracking
DFBA: Data Free Backdoor Attacks
Differentiable Modal Synthesis for Physical Modeling of Planar String Sound and Motion Simulation
Differentially Private Graph Diffusion with Applications in Personalized PageRanks
DiffuBox: Refining 3D Object Detection with Point Diffusion
Diffusion Models With Learned Adaptive Noise
Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies
Diffusion Unlearning Optimization for Robust and Safe Text-to-Image Models
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
Dimension-free Private Mean Estimation for Anisotropic Distributions
DINTR: Tracking via Diffusion-based Interpolation
DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization
Discovering plasticity rules that organize and maintain neural circuits
Discrete Modeling via Boundary Conditional Diffusion Processes
Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems
Dissect Black Box: Interpreting for Rule-Based Explanations in Unsupervised Anomaly Detection
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
Distributionally Robust Performative Prediction
Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation
Distribution Guidance Network for Weakly Supervised Point Cloud Semantic Segmentation
DistrictNet: Decision-aware learning for geographical districting
DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection
Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors
Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
DoGaussian: Distributed-Oriented Gaussian Splatting for Large-Scale 3D Reconstruction Via Gaussian Consensus
Don't Just String Tokens, Stack Them! Improving Multimodal Transformers with Layer Stack
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
Dual-frame Fluid Motion Estimation with Test-time Optimization and Zero-divergence Loss
Dynamic 3D Gaussian Fields for Urban Areas
Dynamic Non-Line-of-Sight Imaging with Mamba Enforced Temporal Consistency
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation
EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding
EAI: Emotional Decision-Making of LLMs in Strategic Games and Ethical Dilemmas
Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision
ECMamba: Consolidating Selective State Space Model with Retinex Guidance for Efficient Multiple Exposure Correction
EEG2Video: Towards Decoding Dynamic Visual Perception from EEG Signals
Efficient Lifelong Model Evaluation in an Era of Rapid Progress
EGODE: An Event-attended Graph ODE Framework for Modeling Rigid Dynamics
EgoSim: An Egocentric Multi-view Simulator for Body-worn Cameras during Human Motion
EigenVI: score-based variational inference with orthogonal function expansions
ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transformer Acceleration
EM Distillation for One-step Diffusion Models
Emergence of heavy tails in homogenized stochastic gradient descent
emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation
Energy-efficient Reinforcement Learning by Discovering Neural Pathways
Enhancing Consistency-Based Image Generation via Adversarialy-Trained Classification and Energy-Based Discrimination
Enhancing Large Language Models via Additional Pre-Training on Principled Synthetic Logic Corpus
Enhancing LLM Reasoning via Vision-Augmented Prompting
Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection
Ensemble sampling for linear bandits: small ensembles suffice
Estimating the Hallucination Rate of Generative AI
ETO:Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses
Evaluating and Eliciting Lateral Thinking of Large Language Models with Situation Puzzles
EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations
Explicit Eigenvalue Reguralization Improves Sharpness-Aware Minimization
Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion
Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks
Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning
FactorizePhys: Effective Spatial-Temporal Attention in Remote Photo-plethysmography through Factorization of Voxel Embeddings
FactorSim: Generative Simulation via Factorized Representation
Fair Kernel K-Means: from Single Kernel towards Multiple Kernel
Fairness and Efficiency in Online Class Matching
Fairness in Social Influence Maximization via Optimal Transport
Fair Wasserstein Coresets
FastDrag: Manipulate Anything in One Step
Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints
Faster Algorithms for User-Level Private Stochastic Convex Optimization
Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
Federated Transformer: Scalable Vertical Federated Learning on Practical Fuzzily Linked Data
FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Differential Aggregation
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity
FilterNet: Harnessing Frequency Filters for Time Series Forecasting
Fine-grained Control of Generative Data Augmentation in IoT Sensing
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning
FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling
FlowLLM: Flow Matching for Material Generation with Learned Base Distributions
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching
FouRA: Fourier Low-Rank Adaptation
Fourier-enhanced Implicit Neural Fusion Network for Multispectral and Hyperspectral Image Fusion
Fractal Patterns May Illuminate the Success of Next-Token Prediction
Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement
FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge
FRHOzen: Loss-Based Data Selection for Targeted Language Model Pre-training
From Text to Trajectory: Exploring Unified Complex Constraint Representation and Decomposition in Safe Reinforcement Learning
FUG: Feature-Universal Graph Contrastive Pre-training for Graphs with Diverse Node Features
Fully Transparent Self-Alignment for Code Generation
Functional Gradient Flows for Constrained Sampling
FuseAnyPart: Diffusion-Driven Facial Parts Swapping via Multiple Reference Images
Future Motion Estimation via Event Sequence Diffusion
G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models
GACL: Exemplar-Free Generalized Analytic Continual Learning
General Articulated Objects Manipulation in Real Images via Part-Aware Diffusion Process
General bounds on the quality of Bayesian coresets
Generalizable Person Re-identification via Balancing Alignment and Uniformity
Generalizablity of Memorization Neural Network
Generalization of Hamiltonian algorithms
Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts
Generative Retrieval Meets Multi-Graded Relevance
Geodesic Optimization for Predictive Shift Adaptation on EEG data
Geometric Analysis of Nonlinear Manifold Clustering
Geometry-aware training of factorized layers in tensor Tucker format
GeoNLF: Geometry guided Pose-Free Neural LiDAR Fields
Gliding over the Pareto Front with Uniform Designs
GLinSAT: The General Linear Satisfiability Neural Network Layer By Accelerated Gradient Descent
Global Rewards in Restless Multi-Armed Bandits
Goal Reduction with Loop-Removal Accelerates RL and Models Human Brain Activity in Goal-Directed Learning
GOUDA: A General Graph Contrastive Learning Framework via Augmentation Unification
Gradient Rewiring for Editable Graph Neural Network Training
Gradient-variation Online Learning under Generalized Smoothness
Grammar-Aligned Decoding
GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction
Graph Diffusion Transformer for Multi-Conditional Molecular Generation
Graph Edit Distance with General Costs Using Neural Set Divergence
Graph Structure Inference with BAM: Introducing the Bilinear Attention Mechanism
GrounDiT: Grounding Diffusion Transformers via Noisy Image Patch Transplantation
GVKF: Gaussian Voxel Kernel Functions for Highly Efficient Surface Reconstruction in Open Scenes
Hamiltonian Score Matching and Generative Flows
HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection
Harmonizing Stochasticity and Determinism: Scene-responsive Diverse Human Motion Prediction
HDR-GS: Efficient High Dynamic Range Novel View Synthesis at 1000x Speed via Gaussian Splatting
Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning
Hierarchical Federated Learning with Multi-Timescale Gradient Correction
High-dimensional (Group) Adversarial Training in Linear Regression
Higher-Order Causal Message Passing for Experimentation Under Unknown Interference
Historical Test-time Prompt Tuning for Vision Foundation Models
Homology Consistency Constrained Efficient Tuning for Vision-Language Models
HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection
How Do Transformers Fill in the Blanks? A Case Study on Matrix Completion
How Transformers Utilize Multi-Head Attention in In-Context Learning? A Case Study on Sparse Linear Regression
Human 3Diffusion: Realistic Avatar Creation via Explicit 3D Consistent Diffusion Models
Human-AI Alignment in Chess with Skill-Aware Attention
Human-level shape inferences: A benchmark for evaluating the 3D understanding of vision models
Human-Readable Fingerprint for Large Language Models
Hybrid Reinforcement Learning Breaks Sample Size Barriers In Linear MDPs
Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers
Hypergraph-Based Fuzzy Assembled Representation for Open-Set 3D Object Retrieval
HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links
Identifiable Shared Component Analysis of Unpaired Multimodal Mixtures
Identifying Causal Effects Under Functional Dependencies
Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
Identifying Latent State-Transition Processes for Individualized Reinforcement Learning
Idiographic Personality Gaussian Process for Psychological Assessment
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token
Image Copy Detection for Diffusion Models
Implicit Precursor Extraction with Expert Retriever for Inorganic Retrosynthesis
Improved off-policy training of diffusion samplers
Improved Particle Approximation Error for Mean Field Neural Networks
Improving Alignment and Robustness with Short Circuiting
Improving Context-Aware Preference Modeling for Language Models
Improving Decision Sparsity
Improving Deep Learning Performance through Constrained Parameter Regularization
Improving optimal control and estimation methods adapted to the noise characteristics of the sensorimotor system
Improving the Learning Capability of Small-size Image Restoration Network by Deep Fourier Shifting Operator over Resource-limited Scene
Improving Viewpoint-Independent Object-Centric Representations through Active Viewpoint Selection
Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation
Injecting Undetectable Backdoors in Deep Learning and Language Models
Instance-Specific Asymmetric Sensitivity in Differential Privacy
Instruction Tuning Large Language Models to Understand Electronic Health Records
Interpretable Mesomorphic Networks for Tabular Data
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual Classification
Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting
IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution
Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models
Iteratively Refined Behavior Regularization for Offline Reinforcement Learning
Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters
JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models
JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images
Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exiting
KptLLM: Unveiling the Power of Large Language Model for Keypoint Comprehension
Label Noise: Ignorance Is Bliss
LAM3D: Large Image-Point Clouds Alignment Model for 3D Reconstruction from Single Image
Large Language Models Must Be Taught to Know What They Don’t Know
LaSCal: Label-Shift Calibration without target labels
Latent Neural Operator for Solving Forward and Inverse PDE Problems
Latent Plan Transformer: Planning as Latent Variable Inference
Lazy Safety Alignment for Large Language Models against Harmful Fine-tuning
LCGen: Mining in Low-Certainty Generation for View-consistent Text-to-3D
Lean Workbook: A large-scale Lean problem set formalized from natural language math problems
Learning 3D Garment Animation from Trajectories of A Piece of Cloth
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
Learning Generalized Linear Programming Value Functions
Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
Learning Group Actions on Latent Representations
Learning Social Welfare Functions
Learning Spatially-Aware Language and Audio Embeddings
Learning the Infinitesimal Generator of Stochastic Diffusion Processes
Learning to be Smooth: An End-to-End Differentiable Particle Smoother
Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality
Learning to Price Homogeneous Data
Learning Versatile Skills with Curriculum Masking
LESS: Label-Efficient and Single-Stage Referring 3D Instance Segmentation
LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization
LG-CAV: Train Any Concept Activation Vector with Language Guidance
LinNet: Linear Network for Efficient Point Cloud Representation Learning
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment
LLMs as Zero-shot Graph Learners: Alignment of GNN Represetantions with LLM Token Embeddings
Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner
Localizing Memorization in SSL Vision Encoders
Lookback Prophet Inequalitites
Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models
Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks
Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
LucidAction: A Hierarchical and Multi-model Dataset for Comprehensive Action Quality Assessment
Lumina-Next : Making Lumina-T2X Stronger and Faster with Next-DiT
LVD-2M: A Long-take Video Dataset with Temporally Dense Captions
Magnet: We Never Know How Text-to-Image Diffusion Models Work, Until We Learn How Vision-Language Models Function
MALT Powers Up Adversarial Attacks
MambaTalk: Co-Speech Gesture Generation with Selective State Space Models
MAmmoTH2: Scaling Instructions from the Web
Many-Shot In-Context Learning
Many-shot Jailbreaking
Mars: Situated Inductive Reasoning in an Open-World Environment
Masked Pre-training Enables Universal Zero-shot Denoiser
MassSpecGym: A benchmark for the discovery and identification of molecules
MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models
MathPile: A Billion-Token-Scale Pretraining Corpus for Math
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
MDAgents: An Adaptive Collaboration of LLMs for Medical Decision Making
Measuring Goal-Directedness
Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset
MedJourney: Benchmark and Evaluation of Large Language Models over Patient Clinical Journey
Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs
MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models
Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement
MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map
MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning
Metric Space Magnitude for Evaluating the Diversity of Latent Representations
MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction
Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games
MimicTalk: Mimicking a personalized and expressive 3D talking face in minutes
MInference: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention
MINI-SEQUENCE TRANSFORMER: Optimizing Intermediate Memory for Long Sequences Training
MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions
Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation
Mixture of neural fields for heterogeneous reconstruction in cryo-EM
Mixture of Tokens: Continuous MoE through Cross-Example Aggregation
MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs
Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA
Model Lego: Creating Models Like Disassembling and Assembling Building Blocks
MoEUT: Mixture-of-Experts Universal Transformers
MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders
MOTE-NAS: Multi-Objective Training-based Estimate for Efficient Neural Architecture Search
MoTE: Reconciling Generalization with Specialization for Visual-Language to Video Knowledge Transfer
MOTI$\mathcal{V}\mathcal{E}$: A Drug-Target Interaction Graph For Inductive Link Prediction
Motion Forecasting in Continuous Driving
MSPE: Multi-Scale Patch Embedding Prompts Vision Transformers to Any Resolution
MTGS: A Novel Framework for Multi-Person Temporal Gaze Following and Social Gaze Prediction
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
Multi-LLM Debate: Framework, Principals, and Interventions
Multimodal foundation world models for generalist embodied agents
Multi-Object Hallucination in Vision Language Models
Multi-scale Consistency for Robust 3D Registration via Hierarchical Sinkhorn Tree
Multistep Distillation of Diffusion Models via Moment Matching
NanoBaseLib: A Multi-Task Benchmark Dataset for Nanopore Sequencing
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
Near-Equivalence Between Bounded Regret and Delay Robustness in Interactive Decision Making
Nearly Minimax Optimal Regret for Multinomial Logistic Bandit
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity
Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs
Needle In A Multimodal Haystack
Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
Neural Fluidic System Design and Control with Differentiable Simulation
Neural Gaffer: Relighting Any Object via Diffusion
Neural Localization Fields for Continuous 3D Human Pose and Shape Estimation
Neural P$^3$M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
NeuralPlane: An Efficiently Parallelizable Platform for Fixed-wing Aircraft Control with Reinforcement Learning
Neural Signed Distance Function Inference through Splatting 3D Gaussians Pulled on Zero-Level Set
NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mapping
NeuRodin: A Two-stage Framework for High-Fidelity Neural Surface Reconstruction
Never Miss A Beat: An Efficient Recipe for Context Window Extension of Large Language Models with Consistent “Middle” Enhancement
NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updates
NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
Non-Euclidean Mixture Model for Social Network Embedding
Non-geodesically-convex optimization in the Wasserstein space
Non-parametric classification via expand-and-sparsify representation
Nonparametric Copula Models for Multivariate, Mixed, and Missing Data
Nonparametric Regression for 3D Point Cloud Learning
Not so griddy: Internal representations of RNNs path integrating more than one agent
Novel Object Synthesis via Adaptive Text-Image Harmony
Nuclear Norm Regularization for Deep Learning
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning
ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models
Off-Policy Action Anticipation in Multi-Agent Reinforcement Learning
On $f$-Divergence Principled Domain Adaptation: An Improved Framework
On Differentially Private U Statistics
On Divergence Measures for Training GFlowNets
OneActor: Consistent Subject Generation via Cluster-Conditioned Guidance
OneBit: Towards Extremely Low-bit Large Language Models
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context
One-shot Federated Learning via Synthetic Distiller-Distillate Communication
One-Shot Safety Alignment for Large Language Models via Optimal Dualization
One-to-Multiple: A Progressive Style Transfer Unsupervised Domain-Adaptive Framework for Kidney Tumor Segmentation
On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection
Online Control in Population Dynamics
Online Learning of Delayed Choices
On the Complexity of Identification in Linear Structural Causal Models
On the Effects of Data Scale on Computer Control Agents
On the Expressive Power of Tree-Structured Probabilistic Circuits
On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function
On the Parameter Identifiability of Partially Observed Linear Causal Models
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
On the Sparsity of the Strong Lottery Ticket Hypothesis
On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity
Optimal ablation for model internals
Optimal Classification under Performative Distribution Shift
Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition
OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
Out-of-Distribution Detection with a Single Unconditional Diffusion Model
Out-Of-Distribution Detection with Diversification (Provably)
Overcoming Common Flaws in the Evaluation of Selective Classification Systems
PAC-Bayes-Chernoff bounds for unbounded losses
PageRank Bandits for Link Prediction
Paloma: A Benchmark for Evaluating Language Model Fit
PANORAMIA: Efficient Privacy Auditing of Machine Learning Models without Retraining
ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping
Parallelizing Linear Transformers with the Delta Rule over Sequence Length
Parameter Competition Balancing for Model Merging
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts
PEACE: A Dataset of Pharmaceutical Care for Cancer Pain Analgesia Evaluation and Medication Decision
Performative Control for Linear Dynamical Systems
Perplexity-aware Correction for Robust Alignment with Noisy Preferences
Persistent Homology for High-dimensional Data Based on Spectral Methods
Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments
PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation
Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees
Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling
Policy-shaped prediction: avoiding distractions in model-based RL
Population Predictive Coding: a structured Bayesian inference algorithm
Position Coupling: Leveraging Task Structure for Improved Length Generalization of Transformers
PowerPM: Foundation Model for Power Systems
Practical $0.385$-Approximation for Submodular Maximization Subject to a Cardinality Constraint
Practical Bayesian Algorithm Execution via Posterior Sampling
Predicting Label Distribution from Ternary Labels
Predicting Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data
Preference Alignment with Flow Matching
Preference-based Pure Exploration
Pretrained Optimization Model for Zero-Shot Black Box Optimization
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
ProgressEditor: Simple Progression is All You Need for High-Quality 3D Scene Editing
Protected Test-Time Domain Adaptation via Online Entropy Matching
Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer
Prototypical Hash Encoding for On-the-Fly Fine-Grained Category Discovery
Provable and Efficient Dataset Distillation for Kernel Ridge Regression
Provable Posterior Sampling with Denoising Oracles Through Tilted Transport
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
Provably Efficient Interactive-Grounded Learning with Personalized Reward
Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer
Proving Olympiad Algebraic Inequalities without Human Demonstrations
PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation
Public-data Assisted Private Stochastic Optimization: Power and Limitations
Quantifying and Optimizing Global Faithfulness in Persona-driven Role-playing
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
Quasi-Bayes meets Vines
QUEEN: QUantized Efficient ENcoding for Streaming Free-viewpoint Videos
QUEST: Quadruple Multimodal Contrastive Learning with Constraints and Self-Penalization
RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation
Random Representations Outperform Online Continually Learned Representations
Real-Time Selection Under General Constraints via Predictive Inference
Real-time Stereo-based 3D Object Detection for Streaming Perception
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving
REBEL: Reinforcement Learning via Regressing Relative Rewards
Referencing Where to Focus: Improving Visual Grounding with Referential Query
ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs
Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control
Relating Hopfield Networks to Episodic Control
RelBench: A Benchmark for Deep Learning on Relational Databases
Reliable Learning of Halfspaces under Gaussian Marginals
Reproducibility Study of "Explaining RL Decisions with Trajectories"
Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective
Rethinking Score Distillation as a Bridge Between Image Distributions
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox
Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection
Revisiting Few-Shot Object Detection with Vision-Language Models
Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning
RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space
RLE: A Unified Perspective of Data Augmentation for Cross-Spectral Re-Identification
Road Network Representation Learning with the Third Law of Geography
Robust Conformal Prediction Using Privileged Information
Robust Fine-tuning of Zero-shot Models via Variance Reduction
Rule Based Rewards for Fine-Grained Safety Behavior in LLMs
Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts
RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models
SA3DIP: Segment Any 3D Instance with Potential 3D Priors
SafeSora: Towards Safety Alignment of Text2Video Generation via a Human Preference Dataset
SAND: Smooth imputation of sparse and noisy functional data with Transformer networks
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
Scalable and Effective Arithmetic Tree Generation for RL-Driven Adder and Multiplier Designs
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
Scalable Early Childhood Reading Performance Prediction
Scalable Optimization in the Modular Norm
Scala: Scalable Representation Learning for Vision Transformer
Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits
Scaling laws for learning with real and surrogate data
Scaling Laws in Linear Regression: Compute, Parameters, and Data
Scaling White-Box Transformers for Vision
SCaR: Refining Skill Chaining for Long-Horizon Robotic Manipulation via Dual Regularization
SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout
Schrodinger Bridge Flow for Unpaired Data Translation
Score-based generative models are provably robust: an uncertainty quantification perspective
SD-Eval: A Benchmark Dataset for Spoken Dialogue Understanding Beyond Words
Seek Commonality but Preserve Differences: Dissected Dynamics Modeling for Multi-modal Visual RL
Segment Any Change
SEL-BALD: Deep Bayesian Active Learning for Selective Labeling with Instance Rejection
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels
SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data
Semi-supervised Multi-label Learning with Balanced Binary Angular Margin Loss
Sequential Harmful Shift Detection Without Labels
SGD vs GD: Rank Deficiency in Linear Networks
SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation
Shaping the distribution of neural responses with interneurons in a recurrent circuit model
Shared Autonomy with IDA: Interventional Diffusion Assistance
SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
Similarity-Navigated Conformal Prediction for Graph Neural Networks
Simplifying Latent Dynamics with Softly State-Invariant World Models
SimPO: Simple Preference Optimization with a Reference-Free Reward
Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information
Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover
Slot State Space Models
Smoothed Online Classification can be Harder than Batch Classification
Soft-Label Integration for Robust Toxicity Classification
Solving Minimum-Cost Reach Avoid using Reinforcement Learning
Solving Zero-Sum Markov Games with Continous State via Spectral Dynamic Embedding
SpatialPIN: Enhancing Spatial Reasoning Capabilities of Vision-Language Models through Prompting and Interacting 3D Priors
Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation
Spiking Neural Network as Adaptive Event Stream Slicer
SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers
S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training
Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation
Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective
Stabilizing Linear Passive-Aggressive Online Learning with Weighted Reservoir Sampling
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases
Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence
StepbaQ: Stepping backward as Correction for Quantized Diffusion Models
Stochastic Concept Bottleneck Models
Stochastic Newton Proximal Extragradient Method
Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting
Streaming Detection of Queried Event Start
StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses
Structure Consistent Gaussian Splatting with Matching Prior for Few-shot Novel View Synthesis
Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics
Style Adaptation and Uncertainty Estimation for Multi-source Blended-Target Domain Adaptation
Suppress Content Shift: Better Diffusion Features via Off-the-Shelf Generation Techniques
Swap Regret, Symmetry, and Nash Convergence in Games
Symmetries in Overparametrized Neural Networks: A Mean Field View
T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models
Tackling Uncertain Correspondences for Multi-Modal Entity Alignment
TAIA: Large Language Models are Out-of-Distribution Data Learners
TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight
Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems
TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs
Text2CAD: Generating Sequential CAD Designs from Beginner-to-Expert Level Text Prompts
Text-DiFuse: An Interactive Multi-Modal Image Fusion Framework based on Text-modulated Diffusion Model
Textual Training for the Hassle-Free Removal of Unwanted Visual Data
TFS-NeRF: Template-Free NeRF for Semantic 3D Reconstruction of Dynamic Scene
The Dormant Neuron Phenomenon in Multi-Agent Reinforcement Learning Value Factorization
The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark
The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks
The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
The Limits of Differential Privacy in Online Learning
The Mamba in the Llama: Distilling and Accelerating Hybrid Models
Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks
There is No Silver Bullet: Benchmarking Methods in Predictive Combinatorial Optimization
Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox
Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences
Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis
TinyLUT: Tiny Look-Up Table for Efficient Image Restoration at the Edge
Token Merging for Training-Free Semantic Binding in Text-to-Image Synthesis
TOPA: Extend Large Language Models for Video Understanding via Text-Only Pre-Alignment
TorchOpt: An Efficient Library for Differentiable Optimization
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning
Toward a Theory of Tokenization in LLMs
Towards Combating Frequency Simplicity-biased Learning for Domain Generalization
Towards Explainable Evaluation Metrics for Machine Translation
Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection in Long Sequence
Towards Principled Graph Transformers
Towards Stable Representations for Protein Interface Prediction
Towards the Dynamics of a DNN Learning Symbolic Interactions
Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
Towards Understanding Evolving Patterns in Sequential Data
Towards Understanding Extrapolation: a Causal Lens
Towards Unified One-tower Expression Grounding and Segmentation with Mask Referring Modeling
TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation
Trace is the New AutoDiff: Unlocking Efficient Optimization of Computational Workflows
Trading off Consistency and Dimensionality of Convex Surrogates for Multiclass Classification
Training GNNs in Balance by Dynamic Rescaling
TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration
Transferable Boltzmann Generators
Transformer Efficiently Learns Low-dimensional Target Functions In-context
Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation
Truncated Variance Reduced Value Iteration
Truth is Universal: Robust Detection of Lies in LLMs
UGC: Universal Graph Coarsening
UltraPixel: Advancing Ultra High-Resolution Image Synthesis to New Peaks
Understanding Bias in Visual Datasets
Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling
Understanding the Role of Equivariance in Self-supervised Learning
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling
Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoE
UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections
UNIT: Unifying Image and Text Recognition in One Vision Encoder
Universal Rates of Empirical Risk Minimization
Unlock the Intermittent Control Ability of Model Free Reinforcement Learning
Unravelling in Collaborative Learning
Unsupervised Anomaly Detection in The Presence of Missing Values
UQE: A Query Engine for Unstructured Databases
UrbanDataLayer: A Unified Data Pipeline for Urban Science
Using Surrogates in Covariate-adjusted Response-adaptive Randomization Experiments with Delayed Outcomes
Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training
Variance estimation for compound decisions
Variational Delayed Policy Optimization
Verifiably Robust Conformal Prediction
VFIMamba: Video Frame Interpolation with State Space Models
VideoLLM-MoD: Efficient Video-Language Streaming with Mixture-of-Depths Vision Computation
VidMan: Exploiting Intrinsic Dynamics from Video Diffusion Model for Effective Robot Manipulation
Vision Foundation Model Enables Generalizable Object Pose Estimation
Visual Data Diagnosis and Debiasing with Concept Graphs
Visual Prompt Tuning in Null Space for Continual Learning
Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion
Watermarking Makes Language Models Radioactive
Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models
Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs
WebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
WeiPer: OOD Detection using Weight Perturbations of Class Projections
What can Foundation Models’ Embeddings do?
What is my quantum computer good for? Quantum capability learning with physics-aware neural networks
What Matters in Graph Class Incremental Learning? An Information Preservation Perspective
What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction
What type of inference is planning?
When and How Does Synthetic Data Improve Reasoning Capabilities of Language Models?
When is an Embedding Model More Promising than Another?
When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
Who Evaluates the Evaluations? Objectively Scoring Text-to-Image Prompt Coherence Metrics with T2IScoreScore (TS2)
Why Do We Need Weight Decay in Modern Deep Learning?
Why Go Full? Elevating Federated Learning Through Partial Network Updates
WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models
WindsorML - High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics
xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token
YouDream: Generating Anatomically Controllable Consistent Text-to-3D Animals
You Only Cache Once: Decoder-Decoder Architectures for Language Models
Zero-Shot Image Segmentation via Recursive Normalized Cut on Diffusion Features
Zero-Shot Reinforcement Learning from Low Quality Data
Zipper: Addressing Degeneracy in Algorithm-Agnostic Inference
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving
(ends 7:30 PM)
Break:
Coffee Break
(ends 5:30 PM)

SAT 14 DEC
7:30 a.m.
Registration (East)
(ends 12:00 PM)
Registration (West)
(ends 4:00 PM)
Break:
Coffee Break
(ends 8:30 AM)
8:15 a.m.
Workshop:
UniReps: Unifying Representations in Neural Models
(ends 5:30 PM)
Workshop:
5th Workshop on Self-Supervised Learning: Theory and Practice
(ends 5:30 PM)
Workshop:
Attributing Model Behavior at Scale (ATTRIB)
(ends 5:30 PM)
Workshop:
Audio Imagination: NeurIPS 2024 Workshop AI-Driven Speech, Music, and Sound Generation
(ends 5:30 PM)
Workshop:
3rd Workshop on New Frontiers in Adversarial Machine Learning (AdvML-Frontiers)
(ends 5:30 PM)
Workshop:
Statistical Frontiers in LLMs and Foundation Models
(ends 5:30 PM)
Workshop:
Workshop on Behavioral Machine Learning
(ends 5:30 PM)
Workshop:
Causality and Large Models
(ends 5:30 PM)
Workshop:
AIM-FM: Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond
(ends 5:30 PM)
Workshop:
Workshop on Scalable Continual Learning for Lifelong Foundation Models
(ends 5:30 PM)
Workshop:
Algorithmic Fairness through the lens of Metrics and Evaluation
(ends 5:30 PM)
Workshop:
MATH-AI: The 4th Workshop on Mathematical Reasoning and AI
(ends 5:30 PM)
Workshop:
NeuroAI: Fusing Neuroscience and AI for Intelligent Solutions
(ends 5:30 PM)
Workshop:
Language Gamification
(ends 5:30 PM)
Workshop:
GenAI for Health: Potential, Trust and Policy Compliance
(ends 5:30 PM)
Workshop:
Symmetry and Geometry in Neural Representations
(ends 5:30 PM)
Workshop:
Mathematics of Modern Machine Learning (M3L)
(ends 5:30 PM)
Workshop:
Generative AI and Creativity: A dialogue between machine learning researchers and creative professionals
(ends 5:30 PM)
Workshop:
The Fourth Workshop on Efficient Natural Language and Speech Processing (ENLSP-IV): Highlighting New Architectures for Future Foundation Models
(ends 5:30 PM)
Workshop:
Workshop on Video-Language Models
(ends 5:30 PM)
Workshop:
Pluralistic Alignment Workshop
(ends 5:30 PM)
Workshop:
Table Representation Learning Workshop (TRL)
(ends 5:30 PM)
Workshop:
Workshop on Responsibly Building Next Generation of Multimodal Foundation Models
(ends 5:30 PM)
Workshop:
Fine-Tuning in Modern Machine Learning: Principles and Scalability
(ends 5:30 PM)
Workshop:
Socially Responsible Language Modelling Research (SoLaR)
(ends 5:30 PM)
Workshop:
Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning
(ends 5:30 PM)
Workshop:
Bayesian Decision-making and Uncertainty: from probabilistic and spatiotemporal modeling to sequential experiment design
(ends 5:30 PM)
Workshop:
AI4Mat-2024: NeurIPS 2024 Workshop on AI for Accelerated Materials Design
(ends 5:30 PM)
9 a.m.
Competition:
HAC: The Hacker-Cup AI Competition
(ends 12:00 PM)
Competition:
FAIR Universe – the challenge of handling uncertainties in fundamental science
(ends 12:00 PM)
Competition:
MyoChallenge 2024: Physiological Dexterity and Agility in Bionic Humans
(ends 12:00 PM)
Competition:
Ariel Data Challenge 2024: Extracting exoplanetary signals from the Ariel Space Telescope
(ends 12:00 PM)
9:30 a.m.
Break:
Coffee Break
(ends 10:00 AM)
noon
Break:
Lunch Break
(ends 1:00 PM)
1:30 p.m.
Competition:
Workshop for URGENT 2024 Challenge
(ends 4:30 PM)
Competition:
Auto-Bidding in Large-Scale Auctions: Learning Decision-Making in Uncertain and Competitive Games
(ends 4:30 PM)
Competition:
Lux AI Season 3: Multi-Agent Meta Learning at Scale
(ends 4:30 PM)
Competition:
NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design
(ends 4:30 PM)
3 p.m.
Break:
Coffee Break
(ends 3:30 PM)

SUN 15 DEC
7:30 a.m.
Registration (West)
(ends 12:00 PM)
Break:
Coffee Break
(ends 8:30 AM)
8:15 a.m.
Workshop:
Machine Learning for Systems
(ends 5:30 PM)
Workshop:
ML with New Compute Paradigms
(ends 5:30 PM)
Workshop:
Machine Learning in Structural Biology
(ends 5:30 PM)
Workshop:
Safe Generative AI
(ends 5:30 PM)
Workshop:
Time Series in the Age of Large Models
(ends 5:30 PM)
Workshop:
Multimodal Algorithmic Reasoning Workshop
(ends 5:30 PM)
Workshop:
Foundation Models for Science: Progress, Opportunities, and Challenges
(ends 5:30 PM)
Workshop:
Tackling Climate Change with Machine Learning
(ends 5:30 PM)
Workshop:
NeurIPS 2024 Workshop: Machine Learning and the Physical Sciences
(ends 5:30 PM)
Workshop:
D3S3: Data-driven and Differentiable Simulations, Surrogates, and Solvers
(ends 5:30 PM)
Workshop:
Foundation Model Interventions
(ends 5:30 PM)
Workshop:
Intrinsically Motivated Open-ended Learning (IMOL)
(ends 5:30 PM)
Workshop:
AI for New Drug Modalities
(ends 5:30 PM)
Workshop:
Workshop on Open-World Agents: Synnergizing Reasoning and Decision-Making in Open-World Environments (OWA-2024)
(ends 5:30 PM)
Workshop:
Optimization for ML Workshop
(ends 5:30 PM)
Workshop:
Interpretable AI: Past, Present and Future
(ends 5:30 PM)
Workshop:
Evaluating Evaluations: Examining Best Practices for Measuring Broader Impacts of Generative AI
(ends 5:30 PM)
Workshop:
Regulatable ML: Towards Bridging the Gaps between Machine Learning Research and Regulations
(ends 5:30 PM)
Workshop:
International Workshop on Federated Foundation Models in Conjunction with NeurIPS 2024 (FL@FM-NeurIPS'24)
(ends 5:30 PM)
Workshop:
Scientific Methods for Understanding Neural Networks: Discovering, Validating, and Falsifying Theories of Deep Learning with Experiments
(ends 5:30 PM)
Workshop:
The First Workshop on Large Foundation Models for Educational Assessment
(ends 5:30 PM)
Workshop:
Compositional Learning: Perspectives, Methods, and Paths Forward
(ends 5:30 PM)
Workshop:
NeurIPS'24 Workshop on Causal Representation Learning
(ends 5:30 PM)
Workshop:
NeurIPS 2024 Workshop: Towards Safe & Trustworthy Agents
(ends 5:30 PM)
Workshop:
System-2 Reasoning at Scale
(ends 5:30 PM)
Workshop:
2nd Workshop on Touch Processing: From Data to Knowledge
(ends 5:30 PM)
Workshop:
Workshop on Machine Learning and Compression
(ends 5:30 PM)
Workshop:
Red Teaming GenAI: What Can We Learn from Adversaries?
(ends 5:30 PM)
9 a.m.
Competition:
The Concordia Contest: Advancing the Cooperative Intelligence of Language Agents
(ends 12:00 PM)
Competition:
LLM Merging: Building LLMs Efficiently through Merging
(ends 12:00 PM)
Competition:
Multi-task Challenges for Rain Movie Prediction on the Road to Hi-Res Foundation Models
(ends 12:00 PM)
Competition:
The NeurIPS 2024 LLM Privacy Challenge
(ends 12:00 PM)
9:30 a.m.
Break:
Coffee Break
(ends 10:00 AM)
noon
Break:
Lunch Break
(ends 1:00 PM)
1:30 p.m.
Competition:
BELKA: The Big Encoded Library for Chemical Assessment
(ends 4:30 PM)
Competition:
Edge-LLMs: Edge-Device Large Language Model Competition
(ends 4:30 PM)
Competition:
Erasing the Invisible: A Stress-Test Challenge for Image Watermarks
(ends 4:30 PM)
Competition:
CLAS 2024: The Competition for LLM and Agent Safety
(ends 4:30 PM)
3 p.m.
Break:
Coffee Break
(ends 3:30 PM)