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

728 papers, page 1 of 15

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 2023Graph Representation for Order-Aware Visual Transformation
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 2023Histopathology Whole Slide Image Analysis With Heterogeneous Graph Representation Learning
11. CVPR 2023Improving Graph Representation for Point Cloud Segmentation via Attentive Filtering
12. CVPR 2023Incremental 3D Semantic Scene Graph Prediction From RGB Sequences
13. CVPR 2023Mind the Label Shift of Augmentation-Based Graph OOD Generalization
14. CVPR 2023Multi-Granularity Archaeological Dating of Chinese Bronze Dings Based on a Knowledge-Guided Relation Graph
15. CVPR 2023Robust 3D Shape Classification via Non-Local Graph Attention Network
16. CVPR 2023Sample-Level Multi-View Graph Clustering
17. CVPR 2023TopDiG: Class-Agnostic Topological Directional Graph Extraction From Remote Sensing Images
18. CVPR 2023Transductive Few-Shot Learning With Prototype-Based Label Propagation by Iterative Graph Refinement
19. CVPR 2023TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning With Structure-Trajectory Prompted Reconstruction for Person Re-Identification
20. CVPR 2023Tree Instance Segmentation With Temporal Contour Graph
21. CVPR 2023Turning Strengths Into Weaknesses: A Certified Robustness Inspired Attack Framework Against Graph Neural Networks
22. CVPR 2023VectorFloorSeg: Two-Stream Graph Attention Network for Vectorized Roughcast Floorplan Segmentation
23. CVPR 2023VL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic Scene Graph Prediction in Point Cloud
24. ICLR 2023$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks
25. ICLR 2023$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks
26. ICLR 2023A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
27. ICLR 2023A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps
28. ICLR 2023A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
29. ICLR 2023Agent-based Graph Neural Networks
30. ICLR 2023Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
31. ICLR 2023Are More Layers Beneficial to Graph Transformers?
32. ICLR 2023AutoGT: Automated Graph Transformer Architecture Search
33. ICLR 2023Automated Data Augmentations for Graph Classification
34. ICLR 2023AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks
35. ICLR 2023Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs
36. ICLR 2023Characterizing the Influence of Graph Elements
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 2023DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
40. ICLR 2023Do We Really Need Complicated Model Architectures For Temporal Networks?
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 2023Energy-based Out-of-Distribution Detection for Graph Neural Networks
45. ICLR 2023Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
46. ICLR 2023ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
47. ICLR 2023Fair Attribute Completion on Graph with Missing Attributes
48. ICLR 2023FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
49. ICLR 2023Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation
50. ICLR 2023Graph Contrastive Learning for Skeleton-based Action Recognition

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.