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 12 of 33

551. NeurIPS 2025EventMG: Efficient Multilevel Mamba-Graph Learning for Spatiotemporal Event Representation
552. NeurIPS 2025EverybodyDance: Bipartite Graph–Based Identity Correspondence for Multi-Character Animation
553. NeurIPS 2025FedIGL: Federated Invariant Graph Learning for Non-IID Graphs
554. NeurIPS 2025FlowPrune: Accelerating Attention Flow Calculation by Pruning Flow Network
555. NeurIPS 2025FoGE: Fock Space inspired encoding for graph prompting
556. NeurIPS 2025GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
557. NeurIPS 2025GD$^2$: Robust Graph Learning under Label Noise via Dual-View Prediction Discrepancy
558. NeurIPS 2025Generative Graph Pattern Machine
559. NeurIPS 2025Geometry-Aware Edge Pooling for Graph Neural Networks
560. NeurIPS 2025Graph Alignment via Birkhoff Relaxation
561. NeurIPS 2025Graph Persistence goes Spectral
562. NeurIPS 2025Graph Your Own Prompt
563. NeurIPS 2025GraphChain: Large Language Models for Large-scale Graph Analysis via Tool Chaining
564. NeurIPS 2025GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data
565. NeurIPS 2025GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
566. NeurIPS 2025Hierarchical Shortest-Path Graph Kernel Network
567. NeurIPS 2025Higher-Order Learning with Graph Neural Networks via Hypergraph Encodings
568. NeurIPS 2025How Does Topology Bias Distort Message Passing in Graph Recommender? A Dirichlet Energy Perspective
569. NeurIPS 2025HubGT: Fast Graph Transformer with Decoupled Hierarchy Labeling
570. NeurIPS 2025HYPERION: Fine-Grained Hypersphere Alignment for Robust Federated Graph Learning
571. NeurIPS 2025HyperMixup: Hypergraph-Augmented with Higher-order Information Mixup
572. NeurIPS 2025Influence Functions for Edge Edits in Non-Convex Graph Neural Networks
573. NeurIPS 2025IPSI: Enhancing Structural Inference with Automatically Learned Structural Priors
574. NeurIPS 2025Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models
575. NeurIPS 2025LBMKGC: Large Model-Driven Balanced Multimodal Knowledge Graph Completion
576. NeurIPS 2025Learning Repetition-Invariant Representations for Polymer Informatics
577. NeurIPS 2025Local-Global Coupling Spiking Graph Transformer for Brain Disorders Diagnosis from Two Perspectives
578. NeurIPS 2025Logical Expressiveness of Graph Neural Networks with Hierarchical Node Individualization
579. NeurIPS 2025Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness–Generalization Perspective
580. NeurIPS 2025MaNGO — Adaptable Graph Network Simulators via Meta-Learning
581. NeurIPS 2025Memorization in Graph Neural Networks
582. NeurIPS 2025Mixture of Scope Experts at Test: Generalizing Deeper Graph Neural Networks with Shallow Variants
583. NeurIPS 2025Negative Feedback Really Matters: Signed Dual-Channel Graph Contrastive Learning Framework for Recommendation
584. NeurIPS 2025Network two-sample test for block models
585. NeurIPS 2025NeuroH-TGL: Neuro-Heterogeneity Guided Temporal Graph Learning Strategy for Brain Disease Diagnosis
586. NeurIPS 2025Object-Centric Representation Learning for Enhanced 3D Semantic Scene Graph Prediction
587. NeurIPS 2025On the Stability of Graph Convolutional Neural Networks: A Probabilistic Perspective
588. NeurIPS 2025On topological descriptors for graph products
589. NeurIPS 2025One for All: Universal Topological Primitive Transfer for Graph Structure Learning
590. NeurIPS 2025Optimal Graph Clustering without Edge Density Signals
591. NeurIPS 2025Over-squashing in Spatiotemporal Graph Neural Networks
592. NeurIPS 2025Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning
593. NeurIPS 2025ProfiX: Improving Profile-Guided Optimization in Compilers with Graph Neural Networks
594. NeurIPS 2025Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
595. NeurIPS 2025Pseudo-Riemannian Graph Transformer
596. NeurIPS 2025Refining Norms: A Post-hoc Framework for OOD Detection in Graph Neural Networks
597. NeurIPS 2025Relieving the Over-Aggregating Effect in Graph Transformers
598. NeurIPS 2025Rethinking Tokenized Graph Transformers for Node Classification
599. NeurIPS 2025Revisiting 1-peer exponential graph for enhancing decentralized learning efficiency
600. NeurIPS 2025Revolutionizing Graph Aggregation: From Suppression to Amplification via BoostGCN

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.