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Timezone: America/Los_Angeles |
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MON 9 DEC
noon
(ends 6:00 PM)
TUE 10 DEC
6:30 a.m.
Expo Talk Panel:
(ends 7:30 AM)
Expo Talk Panel:
(ends 7:30 AM)
Expo Talk Panel:
(ends 7:30 AM)
7:30 a.m.
(ends 6:00 PM)
9:30 a.m.
Tutorial:
(ends 12:00 PM)
Tutorial:
(ends 12:00 PM)
Tutorial:
(ends 12:00 PM)
10 a.m.
Expo Workshop:
(ends 11:30 AM)
Expo Workshop:
(ends 11:30 AM)
Expo Workshop:
(ends 11:30 AM)
Expo Workshop:
(ends 11:30 AM)
Expo Workshop:
(ends 11:30 AM)
noon
Expo Talk Panel:
(ends 1:00 PM)
1 p.m.
(ends 1:03 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
Expo Demonstration:
(ends 3:00 PM)
1:30 p.m.
Tutorial:
(ends 4:00 PM)
Tutorial:
(ends 4:00 PM)
Tutorial:
(ends 4:00 PM)
2 p.m.
Expo Talk Panel:
(ends 3:00 PM)
Expo Talk Panel:
(ends 3:00 PM)
Expo Talk Panel:
(ends 3:00 PM)
Expo Talk Panel:
(ends 3:00 PM)
4 p.m.
5:30 p.m.
WED 11 DEC
8:30 a.m.
9:30 a.m.
10 a.m.
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
(ends 11:00 AM)
(ends 11:00 AM)
(ends 11:00 AM)
11 a.m.
Posters 11:00-2:00
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
Evaluating alignment between humans and neural network representations in image-based learning tasks
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models
Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
(ends 2:00 PM)
(ends 11:03 AM)
Expo Talk Panel:
(ends 12:00 PM)
Expo Workshop:
(ends 12:30 PM)
1 p.m.
2:30 p.m.
Expo Talk Panel:
(ends 3:30 PM)
Expo Talk Panel:
(ends 3:30 PM)
Expo Talk Panel:
(ends 3:30 PM)
3:30 p.m.
(ends 4:30 PM)
(ends 4:30 PM)
(ends 4:30 PM)
4:30 p.m.
Posters 4:30-7:30
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model
Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models
TrajCLIP: Pedestrian trajectory prediction method using contrastive learning and idempotent networks
(ends 7:30 PM)
(ends 4:33 PM)
THU 12 DEC
8:30 a.m.
9:30 a.m.
10 a.m.
(ends 11:00 AM)
(ends 11:00 AM)
(ends 11:00 AM)
11 a.m.
Posters 11:00-2:00
MO-DDN: A Coarse-to-Fine Attribute-based Exploration Agent for Multi-Object Demand-driven Navigation
Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models
Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods
DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised $h$-transform
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning
(ends 2:00 PM)
(ends 11:03 AM)
1 p.m.
2:30 p.m.
3:30 p.m.
(ends 4:30 PM)
(ends 4:30 PM)
(ends 4:30 PM)
4:30 p.m.
Posters 4:30-7:30
Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise
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
Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence
(ends 7:30 PM)
(ends 4:33 PM)
7:30 p.m.
(ends 9:30 PM)
FRI 13 DEC
8:30 a.m.
9:30 a.m.
10 a.m.
(ends 11:00 AM)
(ends 11:00 AM)
(ends 11:00 AM)
11 a.m.
Posters 11:00-2:00
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance
(ends 2:00 PM)
1 p.m.
2:30 p.m.
3:30 p.m.
(ends 4:30 PM)
(ends 4:30 PM)
(ends 4:30 PM)
4:30 p.m.
Posters 4:30-7:30
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance
MoTE: Reconciling Generalization with Specialization for Visual-Language to Video Knowledge Transfer
PEACE: A Dataset of Pharmaceutical Care for Cancer Pain Analgesia Evaluation and Medication Decision
Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer
(ends 7:30 PM)
SAT 14 DEC
7:30 a.m.
(ends 12:00 PM)
(ends 4:00 PM)
8:15 a.m.
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
9 a.m.
Competition:
(ends 12:00 PM)
Competition:
(ends 12:00 PM)
Competition:
(ends 12:00 PM)
9:30 a.m.
noon
1:30 p.m.
Competition:
(ends 4:30 PM)
Competition:
(ends 4:30 PM)
3 p.m.
SUN 15 DEC
8:15 a.m.
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
Workshop:
(ends 5:30 PM)
9 a.m.
Competition:
(ends 12:00 PM)
Competition:
(ends 12:00 PM)
9:30 a.m.
noon
1:30 p.m.
3 p.m.