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

1,648 papers, page 1 of 33

1. CVPR 2026Adaptive Learned Image Compression with Graph Neural Networks
2. CVPR 2026Anomaly as Non-Conformity via Training-Free Graph Laplacian Energy Minimization
3. CVPR 2026Beyond Graph Model Reliable VLM Fine-Tuning via Random Graph Adapter
4. CVPR 2026BrepVGAE Variational Graph Autoencoder with Unified Latent Representation for B-rep
5. CVPR 2026BrickNet Graph-Backed Generative Brick Assembly
6. CVPR 2026CIGPose Causal Intervention Graph Neural Network for Whole-Body Pose Estimation
7. CVPR 2026Cross-Slice Knowledge Transfer via Masked Multi-Modal Heterogeneous Graph Contrastive Learning
8. CVPR 2026Dual Graph Regularized Deep Unfolding Network for Guided Depth Map
9. CVPR 2026DynamicGTR Leveraging Graph Topology Representation Preferences to Boost VLM Capabilities
10. CVPR 2026FedSST Rethinking Fair Federated Graph Learning under Structural Shift
11. CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
12. CVPR 2026Global-Aware Edge Prioritization for Pose Graph Initialization
13. CVPR 2026Graph Attention Prototypical Network for Robust Few-Shot Classification
14. CVPR 2026GraPHFormer A Multimodal Graph Persistent Homology Transformer for the Analysis
15. CVPR 2026GSNR Graph Smooth Null-Space Representation for Inverse Problems
16. CVPR 2026Learning Scene Coordinate Reconstruction from Unposed Images via Pose Graph
17. CVPR 2026PP-Brep Few-Shot B-rep Classification with Hybrid Graph Representation
18. CVPR 2026RoboTAG End-to-end Robot Pose Estimation via Topological Alignment Graph
19. CVPR 2026Semantic Derivative Flow Graph-Guided Diffusion for Controllable Instance Interactions
20. CVPR 2026Solvability of the Viewing Graph Under the Affine Camera Model
21. CVPR 2026STRNet Visual Navigation with Spatio-Temporal Representation through Dynamic Graph Aggregation
22. CVPR 2026Structural Graph Probing of Vision-Language Models
23. CVPR 2026Variational Graph-based Normal Integration
24. CVPR 2026Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor
25. ICLR 2026A Function-Centric Graph Neural Network Approach for Predicting Electron Densities
26. ICLR 2026AdS-GNN - a Conformally Equivariant Graph Neural Network
27. ICLR 2026Any-Subgroup Equivariant Networks via Symmetry Breaking
28. ICLR 2026Certified Evaluation of Model-Level Explanations for Graph Neural Networks
29. ICLR 2026Confident Block Diagonal Structure-Aware Invariable Graph Completion for Incomplete Multi-view Clustering
30. ICLR 2026Dynamic Kernel Graph Sparsifiers
31. ICLR 2026Escaping the Homophily Trap: A Threshold-free Graph Outlier Detection Framework via Clustering-guided Edge Reweighting
32. ICLR 2026Federated Graph-Level Clustering Network with Dual Knowledge Separation
33. ICLR 2026Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
34. ICLR 2026Forest-Based Graph Learning for Semi-Supervised Node Classification
35. ICLR 2026Graph homophily booster: Reimagining the role of discrete features in heterophilic graph learning
36. ICLR 2026Graph Mixing Additive Networks
37. ICLR 2026Graph Representational Learning: When Does More Expressivity Hurt Generalization?
38. ICLR 2026Graph Signal Processing Meets Mamba2: Adaptive Filter Bank via Delta Modulation
39. ICLR 2026Graph-based Nearest Neighbors with Dynamic Updates via Random Walks
40. ICLR 2026Graph-Theoretic Intrinsic Reward: Guiding RL with Effective Resistance
41. ICLR 2026GTool: Graph Enhanced Tool Planning with Large Language Model
42. ICLR 2026Improving Long-Range Interactions in Graph Neural Simulators via Hamiltonian Dynamics
43. ICLR 2026Laplacian Kernelized Bandit
44. ICLR 2026Learning from Historical Activations in Graph Neural Networks
45. ICLR 2026Lightweight Transformer for EEG Classification via Balanced Signed Graph Algorithm Unrolling
46. ICLR 2026Multi-Scale Diffusion-Guided Graph Learning with Power-Smoothing Random Walk Contrast for Multi-View Clustering
47. ICLR 2026On The Expressive Power of GNN Derivatives
48. ICLR 2026One for Two: A Unified Framework for Imbalanced Graph Classification via Dynamic Balanced Prototype
49. ICLR 2026Out-of-Distribution Graph Models Merging
50. ICLR 2026ProofFlow: A Dependency Graph Approach to Faithful Proof Autoformalization

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.