Deep learning · graph neural networks papers, 2023–2026

Key findings

• Deep learning · graph neural networks fell from 728 papers in 2023 to 326 in 2026, so interest is cooling.
• NeurIPS publishes the most Deep learning · graph neural networks work: 842 papers from 2023 to 2026, 51% of the four-venue total.
• The fastest-growing overlap is with Datasets and Benchmarks: papers tagged with both rose from 9 in 2023 to 20 in 2026.
• Among the 11 topics under Deep Learning, it ranks #5 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 0.4x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A New Perspective on Target-Conditioned Structural Dynamics for Link Prediction in Dynamic Graphs
• ICML 2026A Graph Foundation Model with Cross-Modal Alignment and Modality-Aware Expert Fusion for Multi-Modal Graphs
• ICLR 2026Laplacian Kernelized Bandit
• CVPR 2026Gamba Mamba-based graph convolutional network with dynamic graph topology learning
• NeurIPS 2025Depth-Width Tradeoffs for Transformers on Graph Tasks
• ICML 2025A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
• ICLR 2025Factor Graph-based Interpretable Neural Networks
• CVPR 2025Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
• NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
• ICML 2024A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Learning Structure-from-Motion with Graph Attention Networks
• NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
• ICML 2023A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
• ICLR 2023Anti-Symmetric DGN: a stable architecture for Deep Graph Networks
• CVPR 2023An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity
• NeurIPS 2026A Topological Encoder Decoder Framework for Temporal Graph Learning
• ICML 2026A Graphop Analysis of Graph Neural Networks on Sparse Graphs: Generalization and Universal Approximation
• ICLR 2026GTool: Graph Enhanced Tool Planning with Large Language Model
• CVPR 2026GSNR Graph Smooth Null-Space Representation for Inverse Problems

All Deep learning · graph neural networks papers

1,648 papers, page 10 of 33

451. ICML 2025Graph-Based Algorithms for Diverse Similarity Search
452. ICML 2025Graph4MM: Weaving Multimodal Learning with Structural Information
453. ICML 2025GraphGPT: Generative Pre-trained Graph Eulerian Transformer
454. ICML 2025Griffin: Towards a Graph-Centric Relational Database Foundation Model
455. ICML 2025GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers
456. ICML 2025Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks
457. ICML 2025Hgformer: Hyperbolic Graph Transformer for Collaborative Filtering
458. ICML 2025HGOT: Self-supervised Heterogeneous Graph Neural Network with Optimal Transport
459. ICML 2025Hierarchical Graph Tokenization for Molecule-Language Alignment
460. ICML 2025How Expressive are Knowledge Graph Foundation Models?
461. ICML 2025How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
462. ICML 2025Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations
463. ICML 2025HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks
464. ICML 2025Implicit degree bias in the link prediction task
465. ICML 2025Implicit Subgraph Neural Network
466. ICML 2025Improved Approximations for Hard Graph Problems using Predictions
467. ICML 2025Improved Expressivity of Hypergraph Neural Networks through High-Dimensional Generalized Weisfeiler-Leman Algorithms
468. ICML 2025Improving Soft Unification with Knowledge Graph Embedding Methods
469. ICML 2025Improving the Effective Receptive Field of Message-Passing Neural Networks
470. ICML 2025iN2V: Bringing Transductive Node Embeddings to Inductive Graphs
471. ICML 2025Instance Correlation Graph-based Naive Bayes
472. ICML 2025Large Language-Geometry Model: When LLM meets Equivariance
473. ICML 2025Learn Beneficial Noise as Graph Augmentation
474. ICML 2025Learnable Spatial-Temporal Positional Encoding for Link Prediction
475. ICML 2025Learning Latent Graph Structures and their Uncertainty
476. ICML 2025Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
477. ICML 2025LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
478. ICML 2025Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification
479. ICML 2025ML$^2$-GCL: Manifold Learning Inspired Lightweight Graph Contrastive Learning
480. ICML 2025Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment
481. ICML 2025Multi-View Graph Clustering via Node-Guided Contrastive Encoding
482. ICML 2025N2GON: Neural Networks for Graph-of-Net with Position Awareness
483. ICML 2025No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets
484. ICML 2025Nonparametric Teaching for Graph Property Learners
485. ICML 2025On Measuring Long-Range Interactions in Graph Neural Networks
486. ICML 2025Open Your Eyes: Vision Enhances Message Passing Neural Networks in Link Prediction
487. ICML 2025Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models
488. ICML 2025PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
489. ICML 2025Position: Graph Matching Systems Deserve Better Benchmarks
490. ICML 2025Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived
491. ICML 2025Positional Encoding meets Persistent Homology on Graphs
492. ICML 2025Primal-Dual Neural Algorithmic Reasoning
493. ICML 2025Primphormer: Efficient Graph Transformers with Primal Representations
494. ICML 2025Propagate and Inject: Revisiting Propagation-Based Feature Imputation for Graphs with Partially Observed Features
495. ICML 2025Pruning for GNNs: Lower Complexity with Comparable Expressiveness
496. ICML 2025Redundancy Undermines the Trustworthiness of Self-Interpretable GNNs
497. ICML 2025RelGNN: Composite Message Passing for Relational Deep Learning
498. ICML 2025ResearchTown: Simulator of Human Research Community
499. ICML 2025Rethinking Time Encoding via Learnable Transformation Functions
500. ICML 2025Rhomboid Tiling for Geometric Graph Deep Learning

FAQ

How many Deep learning · graph neural networks papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,648 in total: 728 in 2023, 297 in 2024, 297 in 2025, 326 in 2026.

How many Deep learning · graph neural networks papers are at NeurIPS 2026?

NeurIPS 2026 has 102 Deep learning · graph neural networks papers, versus 91 the year before.

How many Deep learning · graph neural networks papers are at ICLR 2026?

ICLR 2026 has 32 Deep learning · graph neural networks papers, versus 50 the year before.

How many Deep learning · graph neural networks papers are at ICML 2026?

ICML 2026 has 168 Deep learning · graph neural networks papers, versus 141 the year before.

How many Deep learning · graph neural networks papers are at CVPR 2026?

CVPR 2026 has 24 Deep learning · graph neural networks papers, versus 15 the year before.

Which conference publishes the most Deep learning · graph neural networks papers?

NeurIPS, with 842 papers from 2023 to 2026.