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 18 of 33

851. NeurIPS 2024InstructG2I: Synthesizing Images from Multimodal Attributed Graphs
852. NeurIPS 2024Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors
853. NeurIPS 2024IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors
854. NeurIPS 2024Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level
855. NeurIPS 2024Iterative Methods via Locally Evolving Set Process
856. NeurIPS 2024Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval
857. NeurIPS 2024Knowledge Graph Completion by Intermediate Variables Regularization
858. NeurIPS 2024Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Cases
859. NeurIPS 2024Learning on Large Graphs using Intersecting Communities
860. NeurIPS 2024Learning rigid-body simulators over implicit shapes for large-scale scenes and vision
861. NeurIPS 2024Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers
862. NeurIPS 2024Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images
863. NeurIPS 2024LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings
864. NeurIPS 2024Logical characterizations of recurrent graph neural networks with reals and floats
865. NeurIPS 2024Long-range Brain Graph Transformer
866. NeurIPS 2024Long-range Meta-path Search on Large-scale Heterogeneous Graphs
867. NeurIPS 2024Mixture of Link Predictors on Graphs
868. NeurIPS 2024NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
869. NeurIPS 2024Non-convolutional graph neural networks.
870. NeurIPS 2024On provable privacy vulnerabilities of graph representations
871. NeurIPS 2024On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks
872. NeurIPS 2024On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
873. NeurIPS 2024On the Power of Small-size Graph Neural Networks for Linear Programming
874. NeurIPS 2024On the Scalability of GNNs for Molecular Graphs
875. NeurIPS 2024Online Relational Inference for Evolving Multi-agent Interacting Systems
876. NeurIPS 2024Open-Book Neural Algorithmic Reasoning
877. NeurIPS 2024Optimal Algorithms for Learning Partitions with Faulty Oracles
878. NeurIPS 2024Probabilistic Graph Rewiring via Virtual Nodes
879. NeurIPS 2024Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
880. NeurIPS 2024ProG: A Graph Prompt Learning Benchmark
881. NeurIPS 2024Pure Message Passing Can Estimate Common Neighbor for Link Prediction
882. NeurIPS 2024RAGraph: A General Retrieval-Augmented Graph Learning Framework
883. NeurIPS 2024Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach
884. NeurIPS 2024Reproducibility Study Of Learning Fair Graph Representations Via Automated Data Augmentations
885. NeurIPS 2024Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy
886. NeurIPS 2024Rethinking the Capacity of Graph Neural Networks for Branching Strategy
887. NeurIPS 2024Revisiting Score Propagation in Graph Out-of-Distribution Detection
888. NeurIPS 2024Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective
889. NeurIPS 2024Robust Graph Neural Networks via Unbiased Aggregation
890. NeurIPS 2024Scale Equivariant Graph Metanetworks
891. NeurIPS 2024Schur Nets: exploiting local structure for equivariance in higher order graph neural networks
892. NeurIPS 2024Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks
893. NeurIPS 2024Similarity-Navigated Conformal Prediction for Graph Neural Networks
894. NeurIPS 2024Spatio-Spectral Graph Neural Networks
895. NeurIPS 2024SpeAr: A Spectral Approach for Zero-Shot Node Classification
896. NeurIPS 2024Spectral Graph Pruning Against Over-Squashing and Over-Smoothing
897. NeurIPS 2024Spiking Graph Neural Network on Riemannian Manifolds
898. NeurIPS 2024State Space Models on Temporal Graphs: A First-Principles Study
899. NeurIPS 2024Stochastic contextual bandits with graph feedback: from independence number to MAS number
900. NeurIPS 2024Supra-Laplacian Encoding for Transformer on Dynamic Graphs

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.