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 5 of 6

201. ICML 2025Vision Graph Prompting via Semantic Low-Rank Decomposition
202. ICML 2025Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win
203. ICML 2025What Makes a Good Feedforward Computational Graph?
204. ICML 2025When Do LLMs Help With Node Classification? A Comprehensive Analysis
205. ICML 2025WILTing Trees: Interpreting the Distance Between MPNN Embeddings
206. ICML 2025Zero-Shot Generalization of GNNs over Distinct Attribute Domains
207. NeurIPS 20253D-GSRD: 3D Molecular Graph Auto-Encoder with Selective Re-mask Decoding
208. NeurIPS 2025A Little Depth Goes a Long Way: The Expressive Power of Log-Depth Transformers
209. NeurIPS 2025Adjusted Count Quantification Learning on Graphs
210. NeurIPS 2025An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph
211. NeurIPS 2025Association-Focused Path Aggregation for Graph Fraud Detection
212. NeurIPS 2025Coloring Learning for Heterophilic Graph Representation
213. NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
214. NeurIPS 2025DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases
215. NeurIPS 2025Depth-Width Tradeoffs for Transformers on Graph Tasks
216. NeurIPS 2025DGCBench: A Deep Graph Clustering Benchmark
217. NeurIPS 2025DiffLiG: Diffusion-enhanced Liquid Graph with Attention Propagation for Grid-to-Station Precipitation Correction
218. NeurIPS 2025Diffusion-Guided Graph Data Augmentation
219. NeurIPS 2025Distribution Learning Meets Graph Structure Sampling
220. NeurIPS 2025DualEqui: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules
221. NeurIPS 2025Dynamic Configuration for Cutting Plane Separators via Reinforcement Learning on Incremental Graph
222. NeurIPS 2025Effects of Dropout on Performance in Long-range Graph Learning Tasks
223. NeurIPS 2025Enforcing convex constraints in Graph Neural Networks
224. NeurIPS 2025Enhancing Graph Classification Robustness with Singular Pooling
225. NeurIPS 2025EventMG: Efficient Multilevel Mamba-Graph Learning for Spatiotemporal Event Representation
226. NeurIPS 2025EverybodyDance: Bipartite Graph–Based Identity Correspondence for Multi-Character Animation
227. NeurIPS 2025FedIGL: Federated Invariant Graph Learning for Non-IID Graphs
228. NeurIPS 2025FlowPrune: Accelerating Attention Flow Calculation by Pruning Flow Network
229. NeurIPS 2025FoGE: Fock Space inspired encoding for graph prompting
230. NeurIPS 2025GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
231. NeurIPS 2025GD$^2$: Robust Graph Learning under Label Noise via Dual-View Prediction Discrepancy
232. NeurIPS 2025Generative Graph Pattern Machine
233. NeurIPS 2025Geometry-Aware Edge Pooling for Graph Neural Networks
234. NeurIPS 2025Graph Alignment via Birkhoff Relaxation
235. NeurIPS 2025Graph Persistence goes Spectral
236. NeurIPS 2025Graph Your Own Prompt
237. NeurIPS 2025GraphChain: Large Language Models for Large-scale Graph Analysis via Tool Chaining
238. NeurIPS 2025GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data
239. NeurIPS 2025GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
240. NeurIPS 2025Hierarchical Shortest-Path Graph Kernel Network
241. NeurIPS 2025Higher-Order Learning with Graph Neural Networks via Hypergraph Encodings
242. NeurIPS 2025How Does Topology Bias Distort Message Passing in Graph Recommender? A Dirichlet Energy Perspective
243. NeurIPS 2025HubGT: Fast Graph Transformer with Decoupled Hierarchy Labeling
244. NeurIPS 2025HYPERION: Fine-Grained Hypersphere Alignment for Robust Federated Graph Learning
245. NeurIPS 2025HyperMixup: Hypergraph-Augmented with Higher-order Information Mixup
246. NeurIPS 2025Influence Functions for Edge Edits in Non-Convex Graph Neural Networks
247. NeurIPS 2025IPSI: Enhancing Structural Inference with Automatically Learned Structural Priors
248. NeurIPS 2025Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models
249. NeurIPS 2025LBMKGC: Large Model-Driven Balanced Multimodal Knowledge Graph Completion
250. NeurIPS 2025Learning Repetition-Invariant Representations for Polymer Informatics

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.