Deep learning · graph neural networks papers, 2023–2026

Key findings

• Deep learning · graph neural networks fell from 728 papers in 2023 to 326 in 2026, so interest is cooling.
• NeurIPS publishes the most Deep learning · graph neural networks work: 842 papers from 2023 to 2026, 51% of the four-venue total.
• The fastest-growing overlap is with Datasets and Benchmarks: papers tagged with both rose from 9 in 2023 to 20 in 2026.
• Among the 11 topics under Deep Learning, it ranks #5 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 0.4x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A New Perspective on Target-Conditioned Structural Dynamics for Link Prediction in Dynamic Graphs
• ICML 2026A Graph Foundation Model with Cross-Modal Alignment and Modality-Aware Expert Fusion for Multi-Modal Graphs
• ICLR 2026Laplacian Kernelized Bandit
• CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
• NeurIPS 2025Depth-Width Tradeoffs for Transformers on Graph Tasks
• ICML 2025A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
• ICLR 2025Factor Graph-based Interpretable Neural Networks
• CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
• NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
• ICML 2024A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Learning Structure-from-Motion with Graph Attention Networks
• NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
• ICML 2023A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
• ICLR 2023Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
• CVPR 2023An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity
• NeurIPS 2026A Topological Encoder Decoder Framework for Temporal Graph Learning
• ICML 2026A Graphop Analysis of Graph Neural Networks on Sparse Graphs: Generalization and Universal Approximation
• ICLR 2026GTool: Graph Enhanced Tool Planning with Large Language Model
• CVPR 2026GSNR Graph Smooth Null-Space Representation for Inverse Problems

All Deep learning · graph neural networks papers

297 papers, page 1 of 6

1. CVPR 2025Are Spatial-Temporal Graph Convolution Networks for Human Action Recognition Over-Parameterized?
2. CVPR 2025Attribute-Missing Multi-view Graph Clustering
3. CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
4. CVPR 2025Consistent Normal Orientation for 3D Point Clouds via Least Squares on Delaunay Graph
5. CVPR 2025End-to-End HOI Reconstruction Transformer with Graph-based Encoding
6. CVPR 2025FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity
7. CVPR 2025FreeScene: Mixed Graph Diffusion for 3D Scene Synthesis from Free Prompts
8. CVPR 2025GG-SSMs: Graph-Generating State Space Models
9. CVPR 2025GLane3D: Detecting Lanes with Graph of 3D Keypoints
10. CVPR 2025MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images
11. CVPR 2025Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning
12. CVPR 2025NN-Former: Rethinking Graph Structure in Neural Architecture Representation
13. CVPR 2025Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping
14. CVPR 2025PHGC: Procedural Heterogeneous Graph Completion for Natural Language Task Verification in Egocentric Videos
15. CVPR 2025Test-Time Domain Generalization via Universe Learning: A Multi-Graph Matching Approach for Medical Image Segmentation
16. ICLR 2025Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation
17. ICLR 2025Beyond Random Masking: When Dropout meets Graph Convolutional Networks
18. ICLR 2025Bias Mitigation in Graph Diffusion Models
19. ICLR 2025Biologically Plausible Brain Graph Transformer
20. ICLR 2025BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
21. ICLR 2025Centrality-guided Pre-training for Graph
22. ICLR 2025Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
23. ICLR 2025Deep Signature: Characterization of Large-Scale Molecular Dynamics
24. ICLR 2025Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing
25. ICLR 2025Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
26. ICLR 2025DUALFormer: Dual Graph Transformer
27. ICLR 2025Edge Prompt Tuning for Graph Neural Networks
28. ICLR 2025Energy-based Backdoor Defense Against Federated Graph Learning
29. ICLR 2025Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
30. ICLR 2025Factor Graph-based Interpretable Neural Networks
31. ICLR 2025Generalizing Weisfeiler-Lehman Kernels to Subgraphs
32. ICLR 2025Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling
33. ICLR 2025Graph Neural Networks Can (Often) Count Substructures
34. ICLR 2025Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems
35. ICLR 2025Graph Transformers Dream of Electric Flow
36. ICLR 2025Graph-based Document Structure Analysis
37. ICLR 2025HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
38. ICLR 2025Homomorphism Counts as Structural Encodings for Graph Learning
39. ICLR 2025Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
40. ICLR 2025How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
41. ICLR 2025IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
42. ICLR 2025Improving Graph Neural Networks by Learning Continuous Edge Directions
43. ICLR 2025KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks
44. ICLR 2025Learning Graph Invariance by Harnessing Spuriosity
45. ICLR 2025Learning Graph Quantized Tokenizers
46. ICLR 2025Learning Partial Graph Matching via Optimal Partial Transport
47. ICLR 2025Learning system dynamics without forgetting
48. ICLR 2025MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
49. ICLR 2025On the Completeness of Invariant Geometric Deep Learning Models
50. ICLR 2025Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems

FAQ

How many Deep learning · graph neural networks papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,648 in total: 728 in 2023, 297 in 2024, 297 in 2025, 326 in 2026.

How many Deep learning · graph neural networks papers are at NeurIPS 2026?

NeurIPS 2026 has 102 Deep learning · graph neural networks papers, versus 91 the year before.

How many Deep learning · graph neural networks papers are at ICLR 2026?

ICLR 2026 has 32 Deep learning · graph neural networks papers, versus 50 the year before.

How many Deep learning · graph neural networks papers are at ICML 2026?

ICML 2026 has 168 Deep learning · graph neural networks papers, versus 141 the year before.

How many Deep learning · graph neural networks papers are at CVPR 2026?

CVPR 2026 has 24 Deep learning · graph neural networks papers, versus 15 the year before.

Which conference publishes the most Deep learning · graph neural networks papers?

NeurIPS, with 842 papers from 2023 to 2026.