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 14 of 21

651. ICLR 2023Explaining Temporal Graph Models through an Explorer-Navigator Framework
652. ICLR 2023ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion
653. ICLR 2023Fair Attribute Completion on Graph with Missing Attributes
654. ICLR 2023FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
655. ICLR 2023Fundamental Limits in Formal Verification of Message-Passing Neural Networks
656. ICLR 2023GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
657. ICLR 2023GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
658. ICLR 2023Graph Domain Adaptation via Theory-Grounded Spectral Regularization
659. ICLR 2023Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
660. ICLR 2023Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
661. ICLR 2023Graph Neural Networks for Link Prediction with Subgraph Sketching
662. ICLR 2023GReTo: Remedying dynamic graph topology-task discordance via target homophily
663. ICLR 2023Grounding Graph Network Simulators using Physical Sensor Observations
664. ICLR 2023Latent Graph Inference using Product Manifolds
665. ICLR 2023Learnable Graph Convolutional Attention Networks
666. ICLR 2023Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks
667. ICLR 2023Learning Fair Graph Representations via Automated Data Augmentations
668. ICLR 2023Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
669. ICLR 2023Learning Hierarchical Protein Representations via Complete 3D Graph Networks
670. ICLR 2023Learning rigid dynamics with face interaction graph networks
671. ICLR 2023LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
672. ICLR 2023Limitless Stability for Graph Convolutional Networks
673. ICLR 2023Matching receptor to odorant with protein language and graph neural networks
674. ICLR 2023MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
675. ICLR 2023Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
676. ICLR 2023NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
677. ICLR 2023On Compositional Uncertainty Quantification for Seq2seq Graph Parsing
678. ICLR 2023On Representing Linear Programs by Graph Neural Networks
679. ICLR 2023On Representing Mixed-Integer Linear Programs by Graph Neural Networks
680. ICLR 2023Re-parameterizing Your Optimizers rather than Architectures
681. ICLR 2023Rethinking Graph Lottery Tickets: Graph Sparsity Matters
682. ICLR 2023Rethinking the Expressive Power of GNNs via Graph Biconnectivity
683. ICLR 2023REVISITING PRUNING AT INITIALIZATION THROUGH THE LENS OF RAMANUJAN GRAPH
684. ICLR 2023Robust Graph Dictionary Learning
685. ICLR 2023Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
686. ICLR 2023Serving Graph Compression for Graph Neural Networks
687. ICLR 2023Specformer: Spectral Graph Neural Networks Meet Transformers
688. ICLR 2023Strategic Classification with Graph Neural Networks
689. ICLR 2023Subsampling in Large Graphs Using Ricci Curvature
690. ICLR 2023Towards Open Temporal Graph Neural Networks
691. ICLR 2023Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States
692. ICML 2023A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests
693. ICML 2023A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel
694. ICML 2023A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
695. ICML 2023A Large-Scale Study of Probabilistic Calibration in Neural Network Regression
696. ICML 2023Adaptive Smoothing Gradient Learning for Spiking Neural Networks
697. ICML 2023All in a Row: Compressed Convolution Networks for Graphs
698. ICML 2023Alternately Optimized Graph Neural Networks
699. ICML 2023Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels
700. ICML 2023Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process

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.