图神经网络论文趋势 2023–2026
GNN 架构
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,038 篇被归入该主题的论文。
主要结论
- 图神经网络论文从 2023 年的 434 篇降到 2026 年的 183 篇，热度在回落。
- NeurIPS 是发图神经网络论文最多的会议，2023–2026 年共 489 篇，占四个会议总量的 47%。
- 交叉方向里涨得最快的是数据集与基准：同时属于两个主题的论文从 2023 年的 10 篇增至 2026 年的 10 篇。
- 在「图与结构化数据」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的时间序列是 3.2 倍，图神经网络是 0.4 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 251 | 69 | 96 | 18 | 434 |
| 2024 | 89 | 45 | 68 | 6 | 208 |
| 2025 | 75 | 45 | 81 | 12 | 213 |
| 2026 | 74 | 28 | 68 | 13 | 183 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- 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
全部图神经网络论文
共 75 篇，第 2 / 2 页
- NeurIPS 2025RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases
- NeurIPS 2025Refining Norms: A Post-hoc Framework for OOD Detection in Graph Neural Networks
- NeurIPS 2025Relieving the Over-Aggregating Effect in Graph Transformers
- NeurIPS 2025Rethinking Tokenized Graph Transformers for Node Classification
- NeurIPS 2025Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks
- NeurIPS 2025Revisiting 1-peer exponential graph for enhancing decentralized learning efficiency
- NeurIPS 2025Revolutionizing Graph Aggregation: From Suppression to Amplification via BoostGCN
- NeurIPS 2025Robust Explanations of Graph Neural Networks via Graph Curvatures
- NeurIPS 2025Robust Graph Condensation via Classification Complexity Mitigation
- NeurIPS 2025Self-Assembling Graph Perceptrons
- NeurIPS 2025SignFlow Bipartite Subgraph Network For Large-Scale Graph Link Sign Prediction
- NeurIPS 2025SONAR: Long-Range Graph Propagation Through Information Waves
- NeurIPS 2025Sound Logical Explanations for Mean Aggregation Graph Neural Networks
- NeurIPS 2025Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum
- NeurIPS 2025TAMI: Taming Heterogeneity in Temporal Interactions for Temporal Graph Link Prediction
- NeurIPS 2025Taxonomy of reduction matrices for Graph Coarsening
- NeurIPS 2025The Logical Expressiveness of Temporal GNNs via Two-Dimensional Product Logics
- NeurIPS 2025The quest for the GRAph Level autoEncoder (GRALE)
- NeurIPS 2025Towards Generalizable Retina Vessel Segmentation with Deformable Graph Priors
- NeurIPS 2025Towards Multiscale Graph-based Protein Learning with Geometric Secondary Structural Motifs
- NeurIPS 2025Towards Pre-trained Graph Condensation via Optimal Transport
- NeurIPS 2025Training Robust Graph Neural Networks by Modeling Noise Dependencies
- NeurIPS 2025Universally Invariant Learning in Equivariant GNNs
- NeurIPS 2025Unsupervised Federated Graph Learning
- NeurIPS 2025You Only Spectralize Once: Taking a Spectral Detour to Accelerate Graph Neural Network
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查图神经网络在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "graph-neural-networks-topic"}
常见问题
- 2023–2026 年四大会议一共有多少篇图神经网络论文？
- 共 1,038 篇，按年份分别是 2023 年 434 篇、2024 年 208 篇、2025 年 213 篇、2026 年 183 篇。
- NeurIPS 2026 有多少篇图神经网络论文？
- NeurIPS 2026 有 74 篇图神经网络论文，上一届是 75 篇。
- ICLR 2026 有多少篇图神经网络论文？
- ICLR 2026 有 28 篇图神经网络论文，上一届是 45 篇。
- ICML 2026 有多少篇图神经网络论文？
- ICML 2026 有 68 篇图神经网络论文，上一届是 81 篇。
- CVPR 2026 有多少篇图神经网络论文？
- CVPR 2026 有 13 篇图神经网络论文，上一届是 12 篇。
- 哪个会议的图神经网络论文最多？
- NeurIPS，2023–2026 年共 489 篇。