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 4 of 21

151. NeurIPS 2026Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists
152. NeurIPS 2026Invariant Hyperbolic Unfolding: Radial Canonicalization for Label-Free Cross-Graph Link Prediction
153. NeurIPS 2026KG-Guard: Graph-Based Hallucination Detection for Knowledge Base Question Answering
154. NeurIPS 2026Learning Pseudo-Riemannian Manifolds for Heterophilic Graphs via Graph Signature
155. NeurIPS 2026Long-Range Spatio-Temporal Graph Propagation Through Oscillations
156. NeurIPS 2026MCGI: Manifold-Consistent Graph Indexing for Billion-Scale Disk-Resident Vector Search
157. NeurIPS 2026MIRAGE: Hierarchical MI-Surrogate Regulation for Graph Contrastive Learning
158. NeurIPS 2026Multilateral Resistance-Guided Graph Message Passing for Trade Flow Prediction
159. NeurIPS 2026Neighbor-Aware Snapshot-Based Temporal Graph Learning
160. NeurIPS 2026Neural Networks With Dense Weights Are Not Universal Approximators
161. NeurIPS 2026Neutral-atom quantum features as complementary structural encodings for graph learning
162. NeurIPS 2026Normalized Architectures are Natively 4-Bit
163. NeurIPS 2026OgBench: A Framework for Evaluating Graph Neural Networks on Omics Data
164. NeurIPS 2026On Worst-Case Guarantees for Graph-Based Nearest-Neighbor Search
165. NeurIPS 2026Orlicz–Sobolev with Musielak: An Efficient Regularization Approach for Graph-based IPM
166. NeurIPS 2026PATH: A Dual Perspective for High-quality Text-attributed Graph Learning
167. NeurIPS 2026PhySPRING: Structure-Preserving Reduction of Physics-Informed Digital Twins via Graph Neural Networks
168. NeurIPS 2026Pointwise Lipschitz Continuous Graph Algorithms
169. NeurIPS 2026Practical Non-Stationary Graph Gaussian Processes
170. NeurIPS 2026Return to Basics: Very Simple Graph Contrastive Learning via Noise Cancellation Principle
171. NeurIPS 2026Robust Graph Diffusion Model
172. NeurIPS 2026Robust Surrogate Modeling for Explainable Graph Neural Networks
173. NeurIPS 2026Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks
174. NeurIPS 2026Spectral Reversal: Counteracting Singular Value Bias for Graph Prompting
175. NeurIPS 2026SpikeSTAG: A Dendritic Compartmental Spiking Graph Network for Multivariate Time-Series Forecasting
176. NeurIPS 2026SSDGExplainer: Structure-Semantic Dual-Guided Explainer for Graph Neural Networks
177. NeurIPS 2026Toward in Silico Strain Evaluation: A Multimodal Surrogate for Fermentation Dynamics with Metabolic Graph Pretraining
178. NeurIPS 2026Uncertainty-Aware Fuzzy Graph Contrastive Learning
179. NeurIPS 2026WavCIL: Wavelet Coefficient-Domain Invariant Learning for Dynamic Graph OOD Generalization
180. NeurIPS 2026Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them
181. NeurIPS 2026What to Perturb, How to Propagate: A Graph-Guided Transferable Attack on VLP Models
182. NeurIPS 2026When Edge Independence Fails: Joint Graph Diffusion with Latent Sociability Priors
183. NeurIPS 2026When Graph Structure Provably Helps Classification: Non-Asymptotic Recovery Guarantees
184. CVPR 2025Attribute-Missing Multi-view Graph Clustering
185. CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
186. CVPR 2025Consistent Normal Orientation for 3D Point Clouds via Least Squares on Delaunay Graph
187. CVPR 2025Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations
188. CVPR 2025End-to-End HOI Reconstruction Transformer with Graph-based Encoding
189. CVPR 2025FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity
190. CVPR 2025GG-SSMs: Graph-Generating State Space Models
191. CVPR 2025GLane3D: Detecting Lanes with Graph of 3D Keypoints
192. CVPR 2025MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images
193. CVPR 2025Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning
194. CVPR 2025NN-Former: Rethinking Graph Structure in Neural Architecture Representation
195. CVPR 2025Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping
196. ICLR 2025Biologically Plausible Brain Graph Transformer
197. ICLR 2025Bonsai: Gradient-free Graph Condensation for Node Classification
198. ICLR 2025Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing
199. ICLR 2025DUALFormer: Dual Graph Transformer
200. ICLR 2025Edge Prompt Tuning for Graph Neural Networks

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.