Graph Neural Networks papers, 2023–2026

Key findings

• Graph Neural Networks fell from 434 papers in 2023 to 183 in 2026, so interest is cooling.
• NeurIPS publishes the most Graph Neural Networks work: 489 papers from 2023 to 2026, 47% of the four-venue total.
• The fastest-growing overlap is with Datasets and Benchmarks: papers tagged with both rose from 10 in 2023 to 10 in 2026.
• Among the 5 topics under Graph and Structured Data, it ranks #4 by 2026 paper count; the fastest grower in the group, Time Series, is up 3.2x versus 0.4x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Differentiable 3D Scene Graph Metric via Contextual Hellinger Triplet Geometry
• ICML 2026Aitchison Embeddings for Learning Compositional Graph Representations
• ICLR 2026Certified Evaluation of Model-Level Explanations for Graph Neural Networks
• CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
• NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
• ICML 2025Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts
• ICLR 2025Edge Prompt Tuning for Graph Neural Networks
• CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
• NeurIPS 2024[Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework"
• ICML 2024A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
• ICLR 2024Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
• CVPR 2024FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer
• NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
• ICML 2023Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering
• ICLR 2023$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks
• CVPR 2023Adversarially Robust Neural Architecture Search for Graph Neural Networks
• NeurIPS 2026A Topological Encoder Decoder Framework for Temporal Graph Learning
• ICML 2026Any-dimensional invariant universality
• ICLR 2026Laplacian Kernelized Bandit
• CVPR 2026Global-Aware Edge Prioritization for Pose Graph Initialization

All Graph Neural Networks papers

187 papers, page 1 of 4

1. ICLR 2026A Graph Meta-Network for Learning on Kolmogorov–Arnold Networks
2. ICLR 2026AdS-GNN - a Conformally Equivariant Graph Neural Network
3. ICLR 2026Any-Subgroup Equivariant Networks via Symmetry Breaking
4. ICLR 2026Are we measuring oversmoothing in graph neural networks correctly?
5. ICLR 2026Can You Hear Me Now? A Benchmark for Long-Range Graph Propagation
6. ICLR 2026Certified Evaluation of Model-Level Explanations for Graph Neural Networks
7. ICLR 2026DGNet: Learning Spatiotemporal PDEs with Discrete Green Networks
8. ICLR 2026Dynamic Kernel Graph Sparsifiers
9. ICLR 2026Fair Graph Machine Learning under Adversarial Missingness Processes
10. ICLR 2026Full-Graph vs. Mini-Batch Training: Comprehensive Analysis from a Batch Size and Fan-Out Size Perspective
11. ICLR 2026GGBall: Graph Generative Model on Poincaré Ball
12. ICLR 2026Glance for Context: Learning When to Leverage LLMs for Node-Aware GNN-LLM Fusion
13. ICLR 2026GNN Explanations that do not Explain and How to find Them
14. ICLR 2026GNN-as-Judge: Unleashing the Power of LLMs for Graph Few-shot Semi-supervised Learning with GNN Feedback
15. ICLR 2026Is Graph Unlearning Ready for Practice? A Benchmark on Efficiency, Utility, and Forgetting
16. ICLR 2026Laplacian Kernelized Bandit
17. ICLR 2026Learning Exposure Mapping Functions for Inferring Heterogeneous Peer Effects
18. ICLR 2026Learning from Historical Activations in Graph Neural Networks
19. ICLR 2026Lightweight Transformer for EEG Classification via Balanced Signed Graph Algorithm Unrolling
20. ICLR 2026LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks
21. ICLR 2026On The Expressive Power of GNN Derivatives
22. ICLR 2026One for Two: A Unified Framework for Imbalanced Graph Classification via Dynamic Balanced Prototype
23. ICLR 2026Out-of-Distribution Graph Models Merging
24. ICLR 2026Paradigm Shift of GNN Explainer from Label Space to Prototypical Representation Space
25. ICLR 2026Relational Graph Transformer
26. ICLR 2026Relatron: Automating Relational Machine Learning over Relational Databases
27. ICLR 2026TopoFormer: Topology Meets Attention for Graph Learning
28. ICLR 2026Weight Space Representation Learning on Diverse NeRF Architectures
29. ICLR 2025Biologically Plausible Brain Graph Transformer
30. ICLR 2025Bonsai: Gradient-free Graph Condensation for Node Classification
31. ICLR 2025Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing
32. ICLR 2025DUALFormer: Dual Graph Transformer
33. ICLR 2025Edge Prompt Tuning for Graph Neural Networks
34. ICLR 2025Exact Certification of (Graph) Neural Networks Against Label Poisoning
35. ICLR 2025Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
36. ICLR 2025Factor Graph-based Interpretable Neural Networks
37. ICLR 2025GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
38. ICLR 2025GOttack: Universal Adversarial Attacks on Graph Neural Networks via Graph Orbits Learning
39. ICLR 2025GRAIN: Exact Graph Reconstruction from Gradients
40. ICLR 2025Graph Neural Networks Can (Often) Count Substructures
41. ICLR 2025Graph Neural Networks Gone Hogwild
42. ICLR 2025Graph Neural Ricci Flow: Evolving Feature from a Curvature Perspective
43. ICLR 2025Graph Sparsification via Mixture of Graphs
44. ICLR 2025Graph Transformers Dream of Electric Flow
45. ICLR 2025Homomorphism Counts as Structural Encodings for Graph Learning
46. ICLR 2025Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
47. ICLR 2025IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
48. ICLR 2025Improving Graph Neural Networks by Learning Continuous Edge Directions
49. ICLR 2025KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks
50. ICLR 2025Learning Efficient Positional Encodings with Graph Neural Networks

FAQ

How many Graph Neural Networks papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,038 in total: 434 in 2023, 208 in 2024, 213 in 2025, 183 in 2026.

How many Graph Neural Networks papers are at NeurIPS 2026?

NeurIPS 2026 has 74 Graph Neural Networks papers, versus 75 the year before.

How many Graph Neural Networks papers are at ICLR 2026?

ICLR 2026 has 28 Graph Neural Networks papers, versus 45 the year before.

How many Graph Neural Networks papers are at ICML 2026?

ICML 2026 has 68 Graph Neural Networks papers, versus 81 the year before.

How many Graph Neural Networks papers are at CVPR 2026?

CVPR 2026 has 13 Graph Neural Networks papers, versus 12 the year before.

Which conference publishes the most Graph Neural Networks papers?

NeurIPS, with 489 papers from 2023 to 2026.