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

434 papers, page 1 of 9

1. CVPR 2023Adaptive Graph Convolutional Subspace Clustering
2. CVPR 2023Adversarially Robust Neural Architecture Search for Graph Neural Networks
3. CVPR 2023An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity
4. CVPR 2023Deep Graph Reprogramming
5. CVPR 2023Deep Graph-Based Spatial Consistency for Robust Non-Rigid Point Cloud Registration
6. CVPR 2023Deep Learning of Partial Graph Matching via Differentiable Top-K
7. CVPR 2023Dynamic Graph Enhanced Contrastive Learning for Chest X-Ray Report Generation
8. CVPR 2023High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition
9. CVPR 2023Highly Confident Local Structure Based Consensus Graph Learning for Incomplete Multi-View Clustering
10. CVPR 2023Incremental 3D Semantic Scene Graph Prediction From RGB Sequences
11. CVPR 2023Mind the Label Shift of Augmentation-Based Graph OOD Generalization
12. CVPR 2023Robust 3D Shape Classification via Non-Local Graph Attention Network
13. CVPR 2023Sample-Level Multi-View Graph Clustering
14. CVPR 2023TopDiG: Class-Agnostic Topological Directional Graph Extraction From Remote Sensing Images
15. CVPR 2023Transductive Few-Shot Learning With Prototype-Based Label Propagation by Iterative Graph Refinement
16. CVPR 2023TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning With Structure-Trajectory Prompted Reconstruction for Person Re-Identification
17. CVPR 2023Turning Strengths Into Weaknesses: A Certified Robustness Inspired Attack Framework Against Graph Neural Networks
18. CVPR 2023VectorFloorSeg: Two-Stream Graph Attention Network for Vectorized Roughcast Floorplan Segmentation
19. ICLR 2023$\mathcal{O}$-GNN: incorporating ring priors into molecular modeling
20. ICLR 2023$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks
21. ICLR 2023A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
22. ICLR 2023A critical look at the evaluation of GNNs under heterophily: Are we really making progress?
23. ICLR 2023A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps
24. ICLR 2023A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
25. ICLR 2023ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
26. ICLR 2023Agent-based Graph Neural Networks
27. ICLR 2023Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel
28. ICLR 2023Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
29. ICLR 2023Are More Layers Beneficial to Graph Transformers?
30. ICLR 2023AutoGT: Automated Graph Transformer Architecture Search
31. ICLR 2023Automated Data Augmentations for Graph Classification
32. ICLR 2023AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks
33. ICLR 2023Backpropagation through Combinatorial Algorithms: Identity with Projection Works
34. ICLR 2023Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs
35. ICLR 2023Characterizing the Influence of Graph Elements
36. ICLR 2023CktGNN: Circuit Graph Neural Network for Electronic Design Automation
37. ICLR 2023Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation
38. ICLR 2023DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks
39. ICLR 2023Do We Really Need Complicated Model Architectures For Temporal Networks?
40. ICLR 2023EAGLE: Large-scale Learning of Turbulent Fluid Dynamics with Mesh Transformers
41. ICLR 2023Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
42. ICLR 2023Effects of Graph Convolutions in Multi-layer Networks
43. ICLR 2023Efficient Model Updates for Approximate Unlearning of Graph-Structured Data
44. ICLR 2023Empowering Graph Representation Learning with Test-Time Graph Transformation
45. ICLR 2023Energy-based Out-of-Distribution Detection for Graph Neural Networks
46. ICLR 2023Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
47. ICLR 2023Explaining Temporal Graph Models through an Explorer-Navigator Framework
48. ICLR 2023ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
49. ICLR 2023Fair Attribute Completion on Graph with Missing Attributes
50. ICLR 2023FoSR: First-order spectral rewiring for addressing oversquashing in GNNs

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.