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

208 papers, page 1 of 5

1. CVPR 2024Adaptive Hyper-graph Aggregation for Modality-Agnostic Federated Learning
2. CVPR 2024DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassembly
3. CVPR 2024FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer
4. CVPR 2024GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs
5. CVPR 2024HHMR: Holistic Hand Mesh Recovery by Enhancing the Multimodal Controllability of Graph Diffusion Models
6. CVPR 2024Learning Structure-from-Motion with Graph Attention Networks
7. ICLR 2024A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
8. ICLR 2024Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
9. ICLR 2024Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
10. ICLR 2024Clifford Group Equivariant Simplicial Message Passing Networks
11. ICLR 2024Conformal Inductive Graph Neural Networks
12. ICLR 2024CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs
13. ICLR 2024Counting Graph Substructures with Graph Neural Networks
14. ICLR 2024Effective Structural Encodings via Local Curvature Profiles
15. ICLR 2024Equivariant Matrix Function Neural Networks
16. ICLR 2024EX-Graph: A Pioneering Dataset Bridging Ethereum and X
17. ICLR 2024Forward Learning of Graph Neural Networks
18. ICLR 2024From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
19. ICLR 2024G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
20. ICLR 2024GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking
21. ICLR 2024GOAt: Explaining Graph Neural Networks via Graph Output Attribution
22. ICLR 2024Graph Lottery Ticket Automated
23. ICLR 2024Graph Metanetworks for Processing Diverse Neural Architectures
24. ICLR 2024Graph Neural Networks for Learning Equivariant Representations of Neural Networks
25. ICLR 2024Graph Parsing Networks
26. ICLR 2024GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks
27. ICLR 2024Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
28. ICLR 2024HiGen: Hierarchical Graph Generative Networks
29. ICLR 2024Hybrid Directional Graph Neural Network for Molecules
30. ICLR 2024Mirage: Model-agnostic Graph Distillation for Graph Classification
31. ICLR 2024MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy
32. ICLR 2024Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
33. ICLR 2024NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
34. ICLR 2024On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters
35. ICLR 2024Online GNN Evaluation Under Test-time Graph Distribution Shifts
36. ICLR 2024Orbit-Equivariant Graph Neural Networks
37. ICLR 2024Partitioning Message Passing for Graph Fraud Detection
38. ICLR 2024PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters
39. ICLR 2024Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
40. ICLR 2024PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
41. ICLR 2024Probabilistically Rewired Message-Passing Neural Networks
42. ICLR 2024Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
43. ICLR 2024Rethinking and Extending the Probabilistic Inference Capacity of GNNs
44. ICLR 2024Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
45. ICLR 2024Robust Angular Synchronization via Directed Graph Neural Networks
46. ICLR 2024SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
47. ICLR 2024TEDDY: Trimming Edges with Degree-based Discrimination Strategy
48. ICLR 2024Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
49. ICLR 2024Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND
50. ICLR 2024VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition

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.