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

489 papers, page 8 of 10

351. NeurIPS 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
352. NeurIPS 2023How Does Adaptive Optimization Impact Local Neural Network Geometry?
353. NeurIPS 2023Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach
354. NeurIPS 2023Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
355. NeurIPS 2023Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization
356. NeurIPS 2023Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings
357. NeurIPS 2023Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
358. NeurIPS 2023Individualized Dosing Dynamics via Neural Eigen Decomposition
359. NeurIPS 2023Information Geometry of the Retinal Representation Manifold
360. NeurIPS 2023Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks
361. NeurIPS 2023Inner Product-based Neural Network Similarity
362. NeurIPS 2023Interpretable Graph Networks Formulate Universal Algebra Conjectures
363. NeurIPS 2023Interpretable Prototype-based Graph Information Bottleneck
364. NeurIPS 2023Investigating how ReLU-networks encode symmetries
365. NeurIPS 2023Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
366. NeurIPS 2023LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
367. NeurIPS 2023Language Semantic Graph Guided Data-Efficient Learning
368. NeurIPS 2023Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
369. NeurIPS 2023Large sample spectral analysis of graph-based multi-manifold clustering
370. NeurIPS 2023Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
371. NeurIPS 2023Latent Graph Inference with Limited Supervision
372. NeurIPS 2023Layer-Neighbor Sampling --- Defusing Neighborhood Explosion in GNNs
373. NeurIPS 2023LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
374. NeurIPS 2023Learning DAGs from Data with Few Root Causes
375. NeurIPS 2023Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
376. NeurIPS 2023Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
377. NeurIPS 2023Learning Large Graph Property Prediction via Graph Segment Training
378. NeurIPS 2023Learning To Dive In Branch And Bound
379. NeurIPS 2023Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets
380. NeurIPS 2023Leveraging the two-timescale regime to demonstrate convergence of neural networks
381. NeurIPS 2023Lie Point Symmetry and Physics-Informed Networks
382. NeurIPS 2023Long Sequence Hopfield Memory
383. NeurIPS 2023MAG-GNN: Reinforcement Learning Boosted Graph Neural Network
384. NeurIPS 2023MathNAS: If Blocks Have a Role in Mathematical Architecture Design
385. NeurIPS 2023Maximum Independent Set: Self-Training through Dynamic Programming
386. NeurIPS 2023MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
387. NeurIPS 2023Modulated Neural ODEs
388. NeurIPS 2023Module-wise Training of Neural Networks via the Minimizing Movement Scheme
389. NeurIPS 2023Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum
390. NeurIPS 2023Multiplication-Free Transformer Training via Piecewise Affine Operations
391. NeurIPS 2023MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data
392. NeurIPS 2023NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
393. NeurIPS 2023NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks
394. NeurIPS 2023Network Regression with Graph Laplacians
395. NeurIPS 2023Neural (Tangent Kernel) Collapse
396. NeurIPS 2023Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions
397. NeurIPS 2023Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity
398. NeurIPS 2023Neural Functional Transformers
399. NeurIPS 2023Neural Graph Generation from Graph Statistics
400. NeurIPS 2023Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem

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.