Graph Transformer

Follow this topic Ask about this topic

Momentum

10 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 63

All topics

Global Communication or Graph-Specific Memory?
Oct 5, 2026Hamed Shirzad, Danica J. SutherlandGraph Neural Networks Transductive Learning
University of British Columbia
Efficient Graph Generation via Direct Prediction and Flow Matching
Oct 4, 2026Susie LuFlow Matching Graph Generation
MIT
Physics-Augmented Graph Transformers for Patch-Antenna Forward and Inverse Design
Oct 4, 2026Avi Epstein, Snir Nehemia, Haim Suchowski +1Physics-Informed GNNs Graph Transformer
Tel Aviv University
Higher-Order Positional Encodings for Graph Representation Learning
Oct 1, 2026Caleb Stam, Aagrim Hoysal, Sanjukta KrishnagopalGraph Representation Learning Positional Encoding
University of California, Santa Barbara
Stable Transformers for Graph Generation
Sep 30, 2026Luca Miglior, Alessio Gravina, Davide BacciuRepresentation Collapse Graph Generation
Department of Computer Science, University of Pisa, Italy
Information Bottleneck-Guided Adaptive Hypergraph Transformer for Brain Disease Diagnosis
Sep 29, 2026Jingxi Feng, Xudong Chen, Yifan Zhang +5Medical Diagnosis Information Bottleneck
Attention Graphons: A Graph Limit Perspective on Graph Transformers
Sep 28, 2026Caio F. Deberaldini Netto, Moshe Eliasof, Luana RuizTransformer Attention Graph Transformer
Johns Hopkins University Baltimore, MD · University of Cambridge Cambridge, UK
MegaGraph: Towards Efficient Training of Large-Scale Graph Transformers with Automated Hybrid Parallelism
Sep 28, 2026Tong Qiao, Ao Zhou, Yingjie Qi +2Distributed Optimization High-Performance Computing
School of Computer Science and Engineering, Beihang University, China · School of Software, Beihang University, China · State Key Laboratory of Complex and Critical Software Environment, Beihang University, China +1
QUARTET: Quad-branch cross-Attention and Random-walk Traces for Enhancing Transformers on Relational Graphs
Sep 22, 2026Kyaw Hpone Myint, Nan Jiang, Xiang Li +4Temporal GNNs Transformer Attention
Capital One
$\text{GSF-}\chi$ : Global Stereochemical Fields for Chiral Graph Transformers
Sep 14, 2026Jiaqing Xie, Yuxin Wang, Xipeng QiuRotary Positional Embeddings Molecular Property Prediction
Shanghai Innovation Institute · Fudan University
ONE CYLinder: A Benchmark for Graph-Based Surrogate Modeling of Unsteady Bluff-Body Flows
Sep 8, 2026Théodore Michel, Antoine Campos, Alban Dujardin +3Surrogate Modeling PDE Surrogate Modeling
Mines Paris PSL University Centre for Material Forming (CEMEF) UMR CNRS, Sophia Antipolis, 06904, France
Graph Learning for Cross-Subject, Cross-Population EEG Emotion Decoding and Model-Derived Spatial-Spectral Neural Signatures
Aug 13, 2026Dongyi He, Bin Jiang, Xiangkai Wang +4Cross-Subject EEG Decoding EEG Decoding
School of Artificial Intelligence, Chongqing University of Technology, Chongqing, 400054, China · School of Smart Health, Chongqing Polytechnic University of Electronic Technology, Chongqing, 401331, China · Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, 222002, China +1
Accounting Graph Transformer for Short-History Multi-KPI Forecasting in Small Businesses
Aug 7, 2026Shrutendra Harsola, Vignesh SubrahmaniamMultivariate Time Series Forecasting Financial Forecasting
Foresight-AI, Intuit Bangalore, India
Graph Machine: Exploring Edge Mechanisms as an Inductive Bias
Aug 7, 2026Lintai HouGraph Structure Learning Neural Algorithmic Reasoning
Iter Labs
MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records
Aug 5, 2026Anirudh Rayas, Yuan Wang, Pavan TuragaHeterogeneous GNNs Clinical Decision Support
Arizona State University, Tempe, AZ, USA · University of South Carolina, Columbia, SC, USA
TopoFormer: Topology Meets Attention for Graph Learning
Jul 30, 2026Md Joshem Uddin, Astrit Tola, Cuneyt Gurcan Akcora +1Graph Representation Learning Graph Classification
Department of Mathematical Science The University of Texas at Dallas Richardson, TX 75080, USA · Department of Mathematics Florida State University Tallahassee, FL 32306, USA · AI Initiative University of Central Florida Orlando, FL 32816, USA
What Makes Graph Unified? Principles and Generative Sliding-Window Transformer for Graph Foundation Models
Jul 30, 2026Dongxiao He, Siqi Liu, Jitao Zhao +3Cross-Domain Transfer Learning Graph Foundation Models
School of Computer Science and Technology Tianjin University Tianjin, China · School of Economics and Management Beijing University of Posts and Telecommunications Beijing, China
THGFM: Dual-Branch Temporal Heterogeneous Graph Fusion Model
Jul 29, 2026Yixin Peng, Diego Collarana, Er Jin +1Graph Neural Networks Temporal Attention
RWTH Aachen University, Aachen, Germany · Fraunhofer FIT, Sankt Augustin, Germany
Labeled Incidence Structures for Native Transformer Modeling of Text, Knowledge Graphs, and Hypergraphs
Jul 29, 2026Mahesh GodavartiRotary Positional Embeddings Knowledge Graphs
A Carrot, Inc
Enhancing Transformer-based Routing by Encoding Distance via Relative Positional Encoding
Jul 21, 2026Leyre Encío, Daniel Fuertes, Carlos R. del-Blanco +1Combinatorial Optimization Positional Encoding
Grupo de Tratamiento de Imágenes, Information Processing and Telecomunications Center, ETSI Telecomunicación, Universidad Politécnica de Madrid, 28040, Madrid, Spain
Adaptive Multi-Expert Graph Transformer for Interpretable EEG-Based Diagnostics
Jul 20, 2026Maryam Rahimimovassagh, Md Elias Hossain, Ivan Garibay +1Electroencephalography Dynamic Graph Learning
Department of Industrial Engineering and Management Systems University of Central Florida, Orlando, FL, USA
A Weisfeiler-Leman Characterization of Global-Attention Graph Transformers for Mixed-Integer Linear Programs
Jul 20, 2026Md Abrar Jahin, Craig A. Knoblock, Jay PujaraMixed-Integer Linear Programming GNN Expressivity
University of Southern California, Los Angeles, CA 90089, USA · USC Information Sciences Institute, Marina del Rey, CA 90292, USA
Node4All: Learning Node Representation Beyond Datasets
Jul 19, 2026Dooho Lee, Jaemin YooGraph Representation Learning Graph SSL
KAIST · Daejeon, Republic of Korea · Seoul National University +1
MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model
Jul 15, 2026Charilaos Papaioannou, Ioannis Tsantilas, Dimitris Giannakakos +9Multi-Task Learning Graph Foundation Models
Higher-Order Cell Tracking Transformer
Jul 13, 2026Jordão Bragantini, Ilan Theodoro, Loïc A. RoyerGraph Transformer Multi-Object Tracking
Biohub San Francisco, CA
Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion
Jul 7, 2026Shervin Khalafi, Igor Krawczuk, Sergio Rozada +3Graph Attention Networks Graph Transformer
University of Pennsylvania · King Juan Carlos University · Stanford University
On Preserving Geometrical Invariance for Superpixel Image Classification using Graph Transformer
Jul 5, 2026Sarabeshwar Balaji, Shubham Mohanty, Akash AnilGraph Neural Networks Invariant Representation Learning
Indian Institute of Science Education and Research Bhopal, Bhopal, Madhya Pradesh, 462066, India
Graph Neural Networks for the Graphical Bootstrap
Jul 3, 2026Rigers Aliaj, Gabriele Dian, Reza Doobary +1Graph Neural Networks High-Energy Physics
Deutsches Elektronen-Synchrotron DESY Hamburg, Germany · Independent Researcher United Kingdom · Department of Mathematical Sciences, Durham University Durham, United Kingdom
X-LogSMask: Expand Transformer for Graph-Structured Data
Jul 2, 2026Leyan Li, Rennong Yang, Zhenxing Zhang +1Graph Attention Networks Graph Representation Learning
Communicability-Inspired Positional Encoding (CIPE)
Jun 24, 2026Yipeng Zhang, Zhongtian Sun, Pietro Liò +1Graph Representation Learning Self-Attention
Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore · School of Computing, University of Kent, Canterbury, Kent CT2 7NZ, UK · Department of Computer Science and Technology, University of Cambridge, 15 JJ Thomson Avenue, Cambridge CB3 0FD, UK

Oct 5, 2026, cs.LGJ/K move · Enter open · S save

Global Communication or Graph-Specific Memory?

Hamed Shirzad, Danica J. Sutherland

University of British Columbia

Graph Neural Networks Transductive Learning Graph Transformer

Open paper AskPDF arXiv

Scalable Graph Transformers are commonly trained and evaluated on static large graphs in a transductive setup. Many scalable Graph Transformer components can be formulated as a constant-size shared memory, similar to virtual nodes, providing compressed information about the whole graph. The counterpart of these models in language models and other domains is justified as the input changes, and this mechanism learns to compress some useful information about the input. In transductive learning on a single fixed graph, however, any shared memory can be seen as a constant at test time. This raises the question of what exactly this shared memory does in this static setup. We give preliminary evidence that optimizing a shared memory directly performs similarly to global communication methods, and so normal local message-passing models can embed similar information in their weights. Thus, these settings may be a poor fit for evaluating global communication in graph neural networks.

Momentum

Related topics

Latest papers 63