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Workshop Thu, Jul 9, 2026 • 4:00 PM – 1:00 AM PDT ROOM 308

Graph Foundation Models: A New Era for Graph Machine Learning

Charilaos Kanatsoulis ⋅ Xingyue Huang ⋅ Ben Finkelshtein ⋅ Michael Bronstein
Project Page [ OpenReview] 

Abstract

Video

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Schedule

Timezone: America/Los_Angeles
5:45 PM
Coffee Break
11:30 PM
Coffee Break
12:45 AM
Closing Remarks
Adapting Tabular Foundation Models for Graph Node-Level Tasks
Dmitry Eremeev ⋅ Gleb Bazhenov ⋅ Oleg Platonov ⋅ Artem Babenko ⋅ Liudmila Prokhorenkova
Anchored SubgraphRAG: Structurally Gated Message Passing for Multi-Hop KG-RAG Retrieval
Konstantin Sturtzkopf ⋅ Lorenzo Giusti ⋅ Pietro Lió
TFMLinker: Universal Link Predictor by Graph In-Context Learning with Tabular Foundation Models
Tianyin Liao ⋅ Chunyu Hu ⋅ Yicheng Sui ⋅ Xingxuan Zhang ⋅ Peng Cui ⋅ Jianxin Li ⋅ Jingyi Liu
Temporal Graph Pattern Machine
Yijun Ma ⋅ Zehong Wang ⋅ Weixiang Sun ⋅ Yanfang Ye
A Fair Evaluation of Graph Foundation Models for Node Property Prediction
Oleg Platonov ⋅ Dmitry Eremeev ⋅ Gleb Bazhenov ⋅ Liudmila Prokhorenkova
Disentangling Dynamics: A Compositional Framework for Temporal Graph Foundation Models
Fabrizio De Castelli ⋅ Alessio Gravina ⋅ Davide Bacciu ⋅ Moshe Eliasof
Beyond Accuracy on RelBench: Item Response Theory Analysis of Relational Deep Learning Benchmarks
Dinesh Katupputhur Ramprasath ⋅ Tom Palczewski ⋅ Joe Meyer ⋅ Roshan R Upendra ⋅ Minghua Li
Neural Networks With Dense Weights Are Not Universal Approximators
Levi Rauchwerger ⋅ Stefanie Jegelka ⋅ Ron Levie
Hydra: Towards Transferable Multi-Task Learning on Temporal Graphs
Kiarash Shamsi ⋅ Farimah Poursafaei ⋅ Tran Gia Bao Ngo ⋅ Reihaneh Rabbany ⋅ Baris Coskunuzer ⋅ Guillaume Rabusseau ⋅ Michael Bronstein ⋅ Shenyang (Andy) Huang ⋅ Cuneyt Akcora
KERMT: Improving Graph Foundation Models for Drug Discovery through Multi-task Fine-Tuning, Data Scaling, and Accelerated Training
Matthew Adrian ⋅ Yunsie Chung ⋅ Kevin Boyd ⋅ Saee Paliwal ⋅ Srimukh Veccham ⋅ Alan Cheng
RelAgent: LLM Agents as Data Scientists for Relational Learning
Xingyue Huang ⋅ Louis Tichelman ⋅ Jinwoo Kim ⋅ Krzysztof Olejniczak ⋅ Ismail Ceylan
Beyond Predefined Schemas: TRACE-KG for Context-Enriched Knowledge Graph Generation
Mohammad S Abolhasani ⋅ Yang Ba ⋅ Yixuan He ⋅ Rong Pan
Edge-aware FlexAttention Network for Efficient Graph Generation
Vincent Jung ⋅ Alba Carballo-Castro ⋅ Yiming Qin ⋅ Lonneke van der Plas ⋅ Pascal Frossard
Linear GCNs Need Better Bias, Not More Expressive Power
Celia Rubio-Madrigal ⋅ Rebekka Burkholz
Deep Neural Sheaf Diffusion
Rémi Bourgerie ⋅ Sarunas Girdzijauskas ⋅ Viktoria Fodor
Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners
Daniel Herbst ⋅ Lea Karbevska ⋅ Divyanshu Kumar ⋅ Akanksha Ahuja ⋅ Fatemeh Gholamzadeh Nasrabadi ⋅ Fabrizio Frasca
Diagnosing Graph Neural Networks: Do They Operate in the Feature Learning Regime and How?
Tao Wen ⋅ Gael C Popescu ⋅ Dawei Zhou ⋅ Yaoqing Yang ⋅ Yujun Yan
Learning Task-Adaptive Connectivity for Graph Transformers
Anita Yang ⋅ Ken-ichi Kawarabayashi
MixUni: Graph Foundation Modeling for Multi-Property Prediction of Molecular Mixtures
Qinan Huang ⋅ Weizhi Xue ⋅ Weizhou Wang ⋅ Mingxuan Cao ⋅ Ian Su
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
Juncheng Wu ⋅ wenlong deng ⋅ Xingxuan Li ⋅ Sheng Liu ⋅ Taomian Mi ⋅ Yifan Peng ⋅ Ziyang Xu ⋅ Yi Liu ⋅ Hyunjin Cho ⋅ Chang-In Choi ⋅ Yihan Cao ⋅ Hui Ren ⋅ Xiang Li ⋅ Xiaoxiao Li ⋅ Yuyin Zhou
LoReC: Rethinking Large Language Models for Graph Data Analysis
Hongyu Zhan ⋅ Qixin Wang ⋅ Yusen Tan ⋅ Haitao YU ⋅ Jingbo Zhou ⋅ Shuai Chen ⋅ Jia Li ⋅ Xiao Tan ⋅ Jun Xia
REL-RAG: Relation-Aware Retrieval-Augmented Generation for Generalizable Knowledge Graph Question Answering
Tianjun Yao ⋅ Haoxuan Li ⋅ Zhiqiang Shen ⋅ Pan Li ⋅ Tongliang Liu ⋅ Kun Zhang
GraphPFN: A Prior-Data Fitted Network for Graph Node-Level Tasks
Dmitry Eremeev ⋅ Oleg Platonov ⋅ Gleb Bazhenov ⋅ Artem Babenko ⋅ Liudmila Prokhorenkova
Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows
Shikun Liu ⋅ Mufei Li ⋅ Dongqi Fu ⋅ Haoyu Wang ⋅ Yinglong Xia ⋅ Hong Li ⋅ Hong Yan ⋅ Pan Li
GILT: An LLM-Free, Tuning-Free Graph Foundational Model for In-Context Learning
Weishuo Ma ⋅ Yanbo Wang ⋅ Xiyuan Wang ⋅ Lei Zou ⋅ Muhan Zhang
Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves
Kartik Tandon ⋅ Julian J Gould ⋅ Tanishq Bhatia ⋅ Francesca Dominici ⋅ Alejandro Ribeiro ⋅ Claudio Battiloro
Rethinking Neural Vehicle Routing as Multi-Agent Decision Making
Jiwoo Son ⋅ Chuanbo Hua ⋅ Federico Berto ⋅ Bongseok Kim ⋅ Jinkyoo Park
Graph Tokenization Meets JEPA: Self-Supervised Learning on Spatial Cell Graphs
Sebastian Birk ⋅ Amirhossein Vahidi ⋅ Mohammad V Sanian ⋅ Arpit Merchant ⋅ Mohammad Lotfollahi
Uni-Bond: Learning Chemical Bonds from Atomic Coordinates
Stepan Pavlenko ⋅ Pavel Maslov ⋅ Ivan B Alexandrovich ⋅ Artem Tsypin ⋅ Alexander Telepov ⋅ Konstantin Ushenin ⋅ Kuzma Khrabrov ⋅ Denis Potapov ⋅ Artur Kadurin
Large-Scale Pretraining unlocks Few-Shot Prediction for Relational Data
Rishabh Ranjan ⋅ Vignesh Kothapalli ⋅ Harshvardhan Agarwal ⋅ Charilaos Kanatsoulis ⋅ Roshan R Upendra ⋅ Tom Palczewski ⋅ Carlos Guestrin ⋅ Jure Leskovec
Providing Context: Enriching Graph Learning Using Language Model Priors
Ziv Mor ⋅ Roy Mahlab ⋅ Moshe Eliasof ⋅ Chaim Baskin
GraphBench: Next-generation Graph Learning Benchmarking
Timo Stoll ⋅ Chendi Qian ⋅ Ben Finkelshtein ⋅ Ali Parviz ⋅ Darius Weber ⋅ Fabrizio Frasca ⋅ Hadar Shavit ⋅ Antoine Siraudin ⋅ Arman Mielke ⋅ Erik Müller ⋅ Marie Anastacio ⋅ Maya Bechler-Speicher ⋅ Michael Bronstein ⋅ Mikhail Galkin ⋅ Holger Hoos ⋅ Mathias Niepert ⋅ Bryan Perozzi ⋅ Jan M Tönshoff ⋅ Christopher Morris
GRATE: Temporal Extensions for Inductive KG Foundation Models via Gated Rotary Attention
Jiaxin Pan ⋅ Osama Mohammed ⋅ Daniel Hernández ⋅ Steffen Staab
What Structural Inductive Bias Helps Transformers Reason Over Knowledge Graphs?
Jonas Petersen ⋅ Camilla Mazzoleni ⋅ Gian-Alessandro Lombardi ⋅ Federico Martelli ⋅ Riccardo Maggioni