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

每年论文数

各会议论文数

按年份和会议统计

图神经网络论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023251699618434
20248945686208
202575458112213
202674286813183

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

全部图神经网络论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 489 篇，第 5 / 10 页

  1. NeurIPS 2024Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors
  2. NeurIPS 2024Iterative Methods via Locally Evolving Set Process
  3. NeurIPS 2024Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval
  4. NeurIPS 2024Knowledge Graph Completion by Intermediate Variables Regularization
  5. NeurIPS 2024Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers
  6. NeurIPS 2024LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings
  7. NeurIPS 2024Long-range Brain Graph Transformer
  8. NeurIPS 2024NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
  9. NeurIPS 2024Non-convolutional graph neural networks.
  10. NeurIPS 2024On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
  11. NeurIPS 2024On the Power of Small-size Graph Neural Networks for Linear Programming
  12. NeurIPS 2024PowerGraph: A power grid benchmark dataset for graph neural networks
  13. NeurIPS 2024Probabilistic Graph Rewiring via Virtual Nodes
  14. NeurIPS 2024ProG: A Graph Prompt Learning Benchmark
  15. NeurIPS 2024RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
  16. NeurIPS 2024RelBench: A Benchmark for Deep Learning on Relational Databases
  17. NeurIPS 2024Reproducibility Study Of Learning Fair Graph Representations Via Automated Data Augmentations
  18. NeurIPS 2024Rethinking the Capacity of Graph Neural Networks for Branching Strategy
  19. NeurIPS 2024Revisiting Score Propagation in Graph Out-of-Distribution Detection
  20. NeurIPS 2024Robust Graph Neural Networks via Unbiased Aggregation
  21. NeurIPS 2024Scale Equivariant Graph Metanetworks
  22. NeurIPS 2024Schur Nets: exploiting local structure for equivariance in higher order graph neural networks
  23. NeurIPS 2024Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks
  24. NeurIPS 2024Similarity-Navigated Conformal Prediction for Graph Neural Networks
  25. NeurIPS 2024Spatio-Spectral Graph Neural Networks
  26. NeurIPS 2024Spiking Graph Neural Network on Riemannian Manifolds
  27. NeurIPS 2024Stochastic contextual bandits with graph feedback: from independence number to MAS number
  28. NeurIPS 2024Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed
  29. NeurIPS 2024The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks
  30. NeurIPS 2024Towards Dynamic Message Passing on Graphs
  31. NeurIPS 2024Towards Principled Graph Transformers
  32. NeurIPS 2024UGC: Universal Graph Coarsening
  33. NeurIPS 2024Understanding Transformer Reasoning Capabilities via Graph Algorithms
  34. NeurIPS 2024Unified Graph Augmentations for Generalized Contrastive Learning on Graphs
  35. NeurIPS 2024What do Graph Neural Networks learn? Insights from Tropical Geometry
  36. NeurIPS 2024What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks
  37. NeurIPS 2024What Matters in Graph Class Incremental Learning? An Information Preservation Perspective
  38. NeurIPS 2024You Only Cache Once: Decoder-Decoder Architectures for Language Models
  39. NeurIPS 2023[Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification
  40. NeurIPS 2023[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
  41. NeurIPS 2023[Re] Variational Neural Cellular Automata
  42. NeurIPS 2023A Fractional Graph Laplacian Approach to Oversmoothing
  43. NeurIPS 2023A graphon-signal analysis of graph neural networks
  44. NeurIPS 2023A Metadata-Driven Approach to Understand Graph Neural Networks
  45. NeurIPS 2023A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
  46. NeurIPS 2023A new perspective on building efficient and expressive 3D equivariant graph neural networks
  47. NeurIPS 2023A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation
  48. NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
  49. NeurIPS 2023A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs
  50. NeurIPS 2023Accelerating Molecular Graph Neural Networks via Knowledge Distillation

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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