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 17 of 21

801. NeurIPS 2023Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach
802. NeurIPS 2023Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
803. NeurIPS 2023Affinity-Aware Graph Networks
804. NeurIPS 2023AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity
805. NeurIPS 2023Analyzing Generalization of Neural Networks through Loss Path Kernels
806. NeurIPS 2023Approximately Equivariant Graph Networks
807. NeurIPS 2023Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
808. NeurIPS 2023Are aligned neural networks adversarially aligned?
809. NeurIPS 2023Are GATs Out of Balance?
810. NeurIPS 2023ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks
811. NeurIPS 2023Asymmetric Certified Robustness via Feature-Convex Neural Networks
812. NeurIPS 2023AutoGO: Automated Computation Graph Optimization for Neural Network Evolution
813. NeurIPS 2023Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks
814. NeurIPS 2023Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis
815. NeurIPS 2023Beyond probability partitions: Calibrating neural networks with semantic aware grouping
816. NeurIPS 2023Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing
817. NeurIPS 2023Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs
818. NeurIPS 2023Certifiably Robust Graph Contrastive Learning
819. NeurIPS 2023Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
820. NeurIPS 2023Cognitive Model Discovery via Disentangled RNNs
821. NeurIPS 2023Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections
822. NeurIPS 2023Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints
823. NeurIPS 2023Compression with Bayesian Implicit Neural Representations
824. NeurIPS 2023Conditional Distribution Function Estimation Using Neural Networks for Censored and Uncensored Data
825. NeurIPS 2023Conformal Prediction for Time Series with Modern Hopfield Networks
826. NeurIPS 2023Contextual Gaussian Process Bandits with Neural Networks
827. NeurIPS 2023ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
828. NeurIPS 2023Convergence of Actor-Critic with Multi-Layer Neural Networks
829. NeurIPS 2023CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics
830. NeurIPS 2023CosNet: A Generalized Spectral Kernel Network
831. NeurIPS 2023CP-SLAM: Collaborative Neural Point-based SLAM System
832. NeurIPS 2023Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective
833. NeurIPS 2023Crystal Structure Prediction by Joint Equivariant Diffusion
834. NeurIPS 2023Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First
835. NeurIPS 2023D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion
836. NeurIPS 2023Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
837. NeurIPS 2023DeepPCR: Parallelizing Sequential Operations in Neural Networks
838. NeurIPS 2023Demystifying Oversmoothing in Attention-Based Graph Neural Networks
839. NeurIPS 2023Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
840. NeurIPS 2023Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer
841. NeurIPS 2023Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection
842. NeurIPS 2023Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks
843. NeurIPS 2023Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power
844. NeurIPS 2023Does a sparse ReLU network training problem always admit an optimum ?
845. NeurIPS 2023Does Graph Distillation See Like Vision Dataset Counterpart?
846. NeurIPS 2023Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
847. NeurIPS 2023Don’t just prune by magnitude! Your mask topology is a secret weapon
848. NeurIPS 2023DSR: Dynamical Surface Representation as Implicit Neural Networks for Protein
849. NeurIPS 2023Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
850. NeurIPS 2023Effective Bayesian Heteroscedastic Regression with Deep 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.