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Workshop Sun, Dec 7, 2025 • 8:00 AM – 5:00 PM PST Exhibit Hall F

New Perspectives in Graph Machine Learning

Zhiyang Wang · Juan Cervino · Luana Ruiz · Alejandro Ribeiro · Stefanie Jegelka · Charilaos Kanatsoulis
Project Page [ OpenReview] 

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Schedule

Timezone: America/Los_Angeles
8:00 AM
Opening Remarks
Zhiyang Wang · Juan Cervino
8:05 AM
Keynote 1 -- Yusu Wang
Yusu Wang
8:50 AM
Beyond Sparse Benchmarks: Evaluating GNNs with Realistic Missing Features
Francesco Ferrini · Veronica Lachi · Antonio Longa · Bruno Lepri · Andrea Passerini · XIN LIU · Manfred Jaeger
9:00 AM
Poster Session 1 and Coffee break
Zhiyang Wang
→ Bridging the Divide: End-to-End Sequence–Graph Learning
Yuen Chen · Yulun Wu · Samuel Sharpe · Igor Melnyk · Nam Nguyen · Furong Huang · C. Bayan Bruss · Rizal Fathony
→ Discovering Transformer Circuits via a Hybrid Attribution and Pruning Framework
Hao Gu · Vibhas Nair · Amrithaa Kumar · Ryan Lagasse · Sean O'Brien
→ Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement
Huidong Liang · Haitz Sáez de Ocáriz Borde · Baskaran Sripathmanathan · Michael Bronstein · Xiaowen Dong
→ Learning (Approximately) Equivariant Networks via Constrained Optimization
Andrei Manolache · Luiz Chamon · Mathias Niepert
→ Biological Pathway Informed Models with Graph Attention Networks (GAT)
Gavin Wong · Ping Ho · Ivan Yeung · Ka Chun Cheung · Simon See
→ Topological Clustering of Aphasic Brain Networks
Jiaying Yi · Jian Yin · Rahul Ghosal · Dirk Ouden · Julius Fridriksson · Rutvik Desai · Yuan Wang
→ Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning
Zifeng Ding · Shenyang Huang · Zeyu Cao · Emma Kondrup · Zachary Yang · Xingyue Huang · Yuan Sui · Zhangdie Yuan · Yuqicheng Zhu · Xianglong Hu · Yuan He · Farimah Poursafaei · Michael Bronstein · Andreas Vlachos
→ Semantic-aware Vicinal Risk Minimization for Long-Tailed Text-Attributed Graphs
Leyao Wang · Yu Wang · Bo Ni · Yuying Zhao · Hanyu Wang · Yao Ma · Tyler Derr
→ Connected Causal Graphs for Real-World Science
Amine M'Charrak · Abbavaram Gowtham Reddy · Thomas Lukasiewicz · Michael Bronstein · Krikamol Muandet
→ Efficient Learning on Large Graphs using a Densifying Regularity Lemma
Jonathan Kouchly · Ben Finkelshtein · Michael Bronstein · Ron Levie
→ Re-evaluating the Advancements of Heterophilic Graph Learning
Sitao Luan · Qincheng Lu · Chenqing Hua · Xinyu Wang · Jiaqi Zhu · Xiao-Wen Chang
→ Metropolis-Scale Road Network Datasets for Fine-Grained Urban Traffic Forecasting
Fedor Velikonivtsev · Oleg Platonov · Gleb Bazhenov · Mikhail Seleznyov · Liudmila Prokhorenkova
→ Exploring Heterophily in Graph-level Tasks
Qinhan Hou · Yilun Zheng · Xichun Zhang · Sitao Luan · Jing Tang
→ FedGraph: A Research Library and Benchmark for Federated Graph Learning
Yuhang Yao · Yuan Li · Xinyi (Cynthia) Fan · Junhao Li · Kay Liu · Yu Yang · Weizhao Jin · Srivatsan Ravi · Philip S Yu · Carlee Joe-Wong
→ Generalizable Insights for Graph Transformers in Theory and Practice
Timo Stoll · Luis Müller · Christopher Morris
→ HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs
Xingyue Huang · Michael Galkin · Michael Bronstein · Ismail Ilkan Ceylan
→ Long-Range Graph Wavelet Networks
Filippo Guerranti · Fabrizio Forte · Simon Markus Geisler · Stephan Günnemann
→ Posterior Label Smoothing for Node Classification
Jaeseung Heo · MoonJeong Park · Dongwoo Kim
→ Equivariant Geometric Scattering Networks via Vector Diffusion Wavelets
Dave Johnson · Rishabh Anand · Smita Krishnaswamy · Michael Perlmutter
→ Predicting Microbial Interactions Using Graph Neural Networks
Elham Gholamzadeh · Kajal Singla · Nico Scherf
→ LGDC: Latent Graph Diffusion via Spectrum-Preserving Coarsening
Nagham Osman · Keyue Jiang · Davide Buffelli · Xiaowen Dong · Laura Toni
→ A Graph Talks, But Who's Listening? Rethinking Evaluations for Graph-Language Models
Soham Petkar · Hari K · Anirudh Vempati · Akshit Sinha · Ponnurangam Kumaraguru · Chirag Agarwal
→ Federated Link Prediction on Dynamic Graphs
Yuhang Yao · Xinyi (Cynthia) Fan · Ryan Rossi · Sungchul Kim · Handong Zhao · Tong Yu · Carlee Joe-Wong
→ Understanding Generalization in Node and Link Prediction
Antonis Vasileiou · Timo Stoll · Christopher Morris
→ Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation
Victor Manuel Tenorio Gomez · Nicolas Zilberstein · Santiago Segarra · Antonio G. Marques
→ Second-Order Tensorial Partial Differential Equations on Graphs
Aref Einizade · Fragkiskos Malliaros · Jhony H. Giraldo
→ Are Large Language Models Good Temporal Graph Learners?
Shenyang Huang · Emma Kondrup · Ali Parviz · Zachary Yang · Zifeng Ding · Michael Bronstein · Reihaneh Rabbany · Guillaume Rabusseau
→ Wasserstein Hypergraph Neural Network
Iulia Duta · Pietro Lió
→ CrediBench : Building Web-Scale Network Datasets for Information Integrity
Emma Kondrup · Sebastian Sabry · Hussein Abdallah · Zachary Yang · James Zhou · Kellin Pelrine · Jean-François Godbout · Michael Bronstein · Reihaneh Rabbany · Shenyang Huang
9:45 AM
Contributed Talk 2
Carlos A Taveras
9:45 AM
Gromov-Wasserstein Graph Coarsening
Carlos A Taveras · Santiago Segarra · Cesar Uribe
9:55 AM
Contributed talk 3
Dhruv Kohli
9:55 AM
Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
Dhruv Kohli · Sawyer Robertson · Gal Mishne · Alex Cloninger
10:10 AM
Keynote 2
Jure Leskovec
10:55 AM
Contributed Talk 4
Songyao Jin
11:05 AM
Contributed Talk 5
Adrian Hayler
11:05 AM
Of Graphs and Tables: Zero-Shot Node Classification with Tabular Foundation Models
Adrian Hayler · Xingyue Huang · Ismail Ilkan Ceylan · Michael Bronstein · Ben Finkelshtein
11:15 AM
Keynote 3
12:00 PM
Lunch Break
1:30 PM
Keynote 4
Nina Miolane
2:15 PM
Keynote 5
Mathias Niepert
3:00 PM
Poster Session 2 and Coffee break
Zhiyang Wang
→ Rethinking Graph Backdoor Defense: A Topological, Coarse-to-Fine Perspective
jiecheng Zhai · Xuzeng Li · Jian Wang · Jiqiang Liu
→ Unrolled Policy Iteration Via Graph Filters
Sergio Rozada · Samuel Rey · Miguel Alcocer Pérez · Gonzalo Mateos · Antonio G. Marques
→ WindMiL: Equivariant Graph Learning for Wind Loading Prediction
Themistoklis Vargiemezis · Charilaos Kanatsoulis · Catherine Gorle
→ Actions Speak Louder than Prompts: A Large-Scale Study of LLMs for Graph Inference
Ben Finkelshtein · Silviu Cucerzan · Sujay Kumar Jauhar · Ryen White
→ Rademacher Meets Colors: More Expressivity, but at What Cost?
Caio Deberaldini Netto · Caterina Graziani · Martin Carrasco · Ehimare Okoyomon · Vahan Martirosyan · Aneeqa Mehrab
→ GNNs Meet Sequence Models Along the Shortest-Path: an Expressive Method for Link Prediction
Francesco Ferrini · Veronica Lachi · Antonio Longa · Bruno Lepri · Andrea Passerini
→ Inductive Transfer Learning for Graph-Based Recommenders
Florian Grötschla · Elia Trachsel · Luca Lanzendörfer · Roger Wattenhofer
→ Learning Joint Embeddings of Function and Process Call Graphs for Malware Detection
Kartikeya Aneja · Nagender Aneja · Murat Kantarcioglu
→ GaLoRA: Parameter-Efficient Graph-Aware LLMs for Node Classification
Mayur Choudhary · Saptarshi Sengupta · Katerina Potika
→ Uncertainty-Aware Message Passing Neural Networks
Alesia Chernikova · Moritz Laber · Narayan Sabhahit · Tina Eliassi-Rad
→ A Generative Framework for Exchangeable Graphs with Global and Local Latent Structure
Daniele Micheletti · Federica Zoe Ricci · Erik Sudderth
→ Spatio-Temporal Directed Graph Learning for Account Takeover Fraud Detection
Mohsen Nayebi Kerdabadi · William A. Byron · xin sun · Amirfarrokh Iranitalab
→ AI-Generated Text Detection using ISGraphs and Graph Neural Networks
Andric Valenzuela · Helena Gomez Adorno · Manuel Montes
→ RELATE: A Schema-Agnostic Cross-Attention Encoder for Multimodal Relational Graphs
Joe Meyer · Divyansha Lachi · Mahmoud Mohammadi · Roshan Upendra · Eva L Dyer · Minghua Li · Tom Palczewski
→ Galois Theory Challenges Weisfeiler Leman: Invariant Features for Symmetric Matrices and Point Clouds
Caio Deberaldini Netto · Beatrix Wen · Thabo Samakhoana · Teresa Huang · Soledad Villar
→ Predict Training Data Quality via Its Geometry in Metric Space
Yang Ba · Mohammad Sadeq Abolhasani · Rong Pan
→ DAG Convolutional Networks
Hamed Ajorlou · Samuel Rey · Gonzalo Mateos
→ Exploiting All Laplacian Eigenvectors for Node Classification with Graph Transformers
Vinam Arora · Divyansha Lachi · Shivashriganesh P. Mahato · Mehdi Azabou · Zihao Chen · Eva L Dyer
→ GNN-Parametrized Diffusion Policies for Wireless Resource Allocation
Yigit Berkay Uslu · Samar Hadou · Shirin Saeedi Bidokhti · Alejandro Ribeiro
→ Turning Tabular Foundation Models into Graph Foundation Models
Dmitry Eremeev · Gleb Bazhenov · Oleg Platonov · Artem Babenko · Liudmila Prokhorenkova
→ Generating Directed Graphs with Dual Attention and Asymmetric Encoding
Alba Carballo Castro · Manuel Madeira · Yiming QIN · Dorina Thanou · Pascal Frossard
→ Interpretable Regime Trajectories via Generative Graph State-Space Models
Jeremy Baffou · Adrien Depeursinge · Dorina Thanou
→ Transferability of Graph Transformers with Convolutional Positional Encodings
Javier Porras-Valenzuela · Zhiyang Wang · Xiaotao Shang · Alejandro Ribeiro
→ Multi-view Graph Condensation via Tensor Decomposition
Nicolas Roque dos Santos · Dawon Ahn · Diego Minatel · Alneu de Andrade Lopes · Vagelis Papalexakis
→ CR-Graphormer: From Cascades to Tokens via Mesoscopic Graph Rewiring
Meher Chaitanya Pindiprolu · My Le · Luana Ruiz
→ Graph Semi-Supervised Learning for Point Classification on Data Manifolds
Caio Deberaldini Netto · Zhiyang Wang · Luana Ruiz
→ A scalable platform to build the data layer of knowledge graph AI
Lucas Vittor · Iñaki Arango · Ayush Noori · Joaquin Polonuer · Marinka Zitnik
→ Efficient and Expressive Graph Neural Networks
Monika Varshney · Tanima Dutta
→ Staleness-based Subgraph Sampling for Training GNNs on Large-Scale Graphs
Limei Wang · Si Zhang · Hanqing Zeng · Hao Wu · Zhigang Hua · Kaveh Hassani · Andrey Malevich · Bo Long · Shuiwang Ji
→ MINAR: Mechanistic Interpretability for Neural Algorithmic Reasoning
Jesse He · Helen Jenne · Max Vargas · Davis Brown · Gal Mishne · Yusu Wang · Henry Kvinge
→ Diffusion-Generated Social Graphs Enhance Bot Detection
Alec Laprevotte · Ryan Lin · Siddhartha Ojha
3:50 PM
Contributed Talk 6
Yifei Wang
3:50 PM
G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning
Xiaojun Guo · Ang Li · Yifei Wang · Stefanie Jegelka · Yisen Wang
4:00 PM
Panel Discussion
Xiaowen Dong · Soledad Villar · Tom Palczewski