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

1,038 papers, page 5 of 21

201. ICLR 2025Exact Certification of (Graph) Neural Networks Against Label Poisoning
202. ICLR 2025Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
203. ICLR 2025Factor Graph-based Interpretable Neural Networks
204. ICLR 2025GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
205. ICLR 2025GOttack: Universal Adversarial Attacks on Graph Neural Networks via Graph Orbits Learning
206. ICLR 2025GRAIN: Exact Graph Reconstruction from Gradients
207. ICLR 2025Graph Neural Networks Can (Often) Count Substructures
208. ICLR 2025Graph Neural Networks Gone Hogwild
209. ICLR 2025Graph Neural Ricci Flow: Evolving Feature from a Curvature Perspective
210. ICLR 2025Graph Sparsification via Mixture of Graphs
211. ICLR 2025Graph Transformers Dream of Electric Flow
212. ICLR 2025Homomorphism Counts as Structural Encodings for Graph Learning
213. ICLR 2025Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
214. ICLR 2025IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
215. ICLR 2025Improving Graph Neural Networks by Learning Continuous Edge Directions
216. ICLR 2025KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks
217. ICLR 2025Learning Efficient Positional Encodings with Graph Neural Networks
218. ICLR 2025Learning Equivariant Non-Local Electron Density Functionals
219. ICLR 2025Learning Graph Invariance by Harnessing Spuriosity
220. ICLR 2025Learning Graph Quantized Tokenizers
221. ICLR 2025Learning Long Range Dependencies on Graphs via Random Walks
222. ICLR 2025Learning Partial Graph Matching via Optimal Partial Transport
223. ICLR 2025Let Your Features Tell The Differences: Understanding Graph Convolution By Feature Splitting
224. ICLR 2025MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
225. ICLR 2025Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
226. ICLR 2025On the Completeness of Invariant Geometric Deep Learning Models
227. ICLR 2025On the Hölder Stability of Multiset and Graph Neural Networks
228. ICLR 2025PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems
229. ICLR 2025Precedence-Constrained Winter Value for Effective Graph Data Valuation
230. ICLR 2025Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features
231. ICLR 2025Scale-Free Graph-Language Models
232. ICLR 2025Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation
233. ICLR 2025SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs
234. ICLR 2025Spectro-Riemannian Graph Neural Networks
235. ICLR 2025Towards a Complete Logical Framework for GNN Expressiveness
236. ICLR 2025Towards Bridging Generalization and Expressivity of Graph Neural Networks
237. ICLR 2025Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming
238. ICLR 2025Valid Conformal Prediction for Dynamic GNNs
239. ICLR 2025When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
240. ICLR 2025When Graph Neural Networks Meet Dynamic Mode Decomposition
241. ICML 2025A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
242. ICML 2025A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Attention Networks
243. ICML 2025A Manifold Perspective on the Statistical Generalization of Graph Neural Networks
244. ICML 2025Adapting Precomputed Features for Efficient Graph Condensation
245. ICML 2025Aggregation Buffer: Revisiting DropEdge with a New Parameter Block
246. ICML 2025Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction
247. ICML 2025Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data
248. ICML 2025AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization
249. ICML 2025Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
250. ICML 2025Beyond Message Passing: Neural Graph Pattern Machine

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.