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

251 papers, page 3 of 6

101. NeurIPS 2023Going beyond persistent homology using persistent homology
102. NeurIPS 2023GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks
103. NeurIPS 2023Graph Clustering with Graph Neural Networks
104. NeurIPS 2023Graph Convolutional Kernel Machine versus Graph Convolutional Networks
105. NeurIPS 2023Graph Denoising Diffusion for Inverse Protein Folding
106. NeurIPS 2023Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
107. NeurIPS 2023Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis
108. NeurIPS 2023Graph of Circuits with GNN for Exploring the Optimal Design Space
109. NeurIPS 2023GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search
110. NeurIPS 2023GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation
111. NeurIPS 2023GSLB: The Graph Structure Learning Benchmark
112. NeurIPS 2023Hierarchical Randomized Smoothing
113. NeurIPS 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
114. NeurIPS 2023How Does Adaptive Optimization Impact Local Neural Network Geometry?
115. NeurIPS 2023Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach
116. NeurIPS 2023Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
117. NeurIPS 2023Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization
118. NeurIPS 2023Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
119. NeurIPS 2023Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
120. NeurIPS 2023Individualized Dosing Dynamics via Neural Eigen Decomposition
121. NeurIPS 2023Information Geometry of the Retinal Representation Manifold
122. NeurIPS 2023Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks
123. NeurIPS 2023Inner Product-based Neural Network Similarity
124. NeurIPS 2023Interpretable Graph Networks Formulate Universal Algebra Conjectures
125. NeurIPS 2023Interpretable Prototype-based Graph Information Bottleneck
126. NeurIPS 2023Investigating how ReLU-networks encode symmetries
127. NeurIPS 2023Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
128. NeurIPS 2023LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
129. NeurIPS 2023Language Semantic Graph Guided Data-Efficient Learning
130. NeurIPS 2023Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
131. NeurIPS 2023Large sample spectral analysis of graph-based multi-manifold clustering
132. NeurIPS 2023Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
133. NeurIPS 2023Latent Graph Inference with Limited Supervision
134. NeurIPS 2023Layer-Neighbor Sampling --- Defusing Neighborhood Explosion in GNNs
135. NeurIPS 2023LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
136. NeurIPS 2023Learning DAGs from Data with Few Root Causes
137. NeurIPS 2023Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
138. NeurIPS 2023Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
139. NeurIPS 2023Learning Large Graph Property Prediction via Graph Segment Training
140. NeurIPS 2023Learning To Dive In Branch And Bound
141. NeurIPS 2023Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets
142. NeurIPS 2023Leveraging the two-timescale regime to demonstrate convergence of neural networks
143. NeurIPS 2023Lie Point Symmetry and Physics-Informed Networks
144. NeurIPS 2023Long Sequence Hopfield Memory
145. NeurIPS 2023MAG-GNN: Reinforcement Learning Boosted Graph Neural Network
146. NeurIPS 2023MathNAS: If Blocks Have a Role in Mathematical Architecture Design
147. NeurIPS 2023Maximum Independent Set: Self-Training through Dynamic Programming
148. NeurIPS 2023MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
149. NeurIPS 2023Modulated Neural ODEs
150. NeurIPS 2023Module-wise Training of Neural Networks via the Minimizing Movement Scheme

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.