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 7 of 21

301. ICML 2025RelGNN: Composite Message Passing for Relational Deep Learning
302. ICML 2025Rethinking Time Encoding via Learnable Transformation Functions
303. ICML 2025ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
304. ICML 2025Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation
305. ICML 2025Scalable Sobolev IPM for Probability Measures on a Graph
306. ICML 2025Self-supervised Adversarial Purification for Graph Neural Networks
307. ICML 2025Signed Laplacians for Constrained Graph Clustering
308. ICML 2025Simple Path Structural Encoding for Graph Transformers
309. ICML 2025Stable Fair Graph Representation Learning with Lipschitz Constraint
310. ICML 2025Supercharging Graph Transformers with Advective Diffusion
311. ICML 2025Test-Time Graph Neural Dataset Search With Generative Projection
312. ICML 2025TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
313. ICML 2025TopInG: Topologically Interpretable Graph Learning via Persistent Rationale Filtration
314. ICML 2025Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph
315. ICML 2025TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks
316. ICML 2025Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
317. ICML 2025Towards characterizing the value of edge embeddings in Graph Neural Networks
318. ICML 2025Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
319. ICML 2025What Makes a Good Feedforward Computational Graph?
320. ICML 2025WILTing Trees: Interpreting the Distance Between MPNN Embeddings
321. ICML 2025Zero-Shot Generalization of GNNs over Distinct Attribute Domains
322. NeurIPS 2025$\texttt{STRCMP}$: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization
323. NeurIPS 2025A CLT for Polynomial GNNs on Community-Based Graphs
324. NeurIPS 2025Adjusted Count Quantification Learning on Graphs
325. NeurIPS 2025An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph
326. NeurIPS 2025Association-Focused Path Aggregation for Graph Fraud Detection
327. NeurIPS 2025Bridging Theory and Practice in Link Representation with Graph Neural Networks
328. NeurIPS 2025Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
329. NeurIPS 2025Depth-Width Tradeoffs for Transformers on Graph Tasks
330. NeurIPS 2025DiffLiG: Diffusion-enhanced Liquid Graph with Attention Propagation for Grid-to-Station Precipitation Correction
331. NeurIPS 2025Effects of Dropout on Performance in Long-range Graph Learning Tasks
332. NeurIPS 2025Enforcing convex constraints in Graph Neural Networks
333. NeurIPS 2025Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
334. NeurIPS 2025Explore In-Context Message Passing Operator for Graph Neural Networks in A Mean Field Game
335. NeurIPS 2025FoGE: Fock Space inspired encoding for graph prompting
336. NeurIPS 2025GD$^2$: Robust Graph Learning under Label Noise via Dual-View Prediction Discrepancy
337. NeurIPS 2025Generative Graph Pattern Machine
338. NeurIPS 2025Geometric Logit Decoupling for Energy-Based Graph Out-of-distribution Detection
339. NeurIPS 2025Geometry-Aware Edge Pooling for Graph Neural Networks
340. NeurIPS 2025GnnXemplar: Exemplars to Explanations - Natural Language Rules for Global GNN Interpretability
341. NeurIPS 2025Graph Alignment via Birkhoff Relaxation
342. NeurIPS 2025Graph Data Selection for Domain Adaptation: A Model-Free Approach
343. NeurIPS 2025Graph Neural Network Based Action Ranking for Planning
344. NeurIPS 2025Graph Persistence goes Spectral
345. NeurIPS 2025Graph Your Own Prompt
346. NeurIPS 2025Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models
347. NeurIPS 2025GraphChain: Large Language Models for Large-scale Graph Analysis via Tool Chaining
348. NeurIPS 2025GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data
349. NeurIPS 2025GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
350. NeurIPS 2025HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations

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.