数据集与基准论文趋势 2023–2026

新数据集与评测协议

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 5,856 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

数据集与基准论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023227162166382937
20244482163183641,346
20256374191893371,582
20266236352754581,991

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

全部数据集与基准论文

共 318 篇,第 7 / 7 页

  1. ICML 2024Trained Random Forests Completely Reveal your Dataset
  2. ICML 2024Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
  3. ICML 2024Transitional Uncertainty with Layered Intermediate Predictions
  4. ICML 2024Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning
  5. ICML 2024Trustless Audits without Revealing Data or Models
  6. ICML 2024Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness
  7. ICML 2024Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias
  8. ICML 2024ULTRAFEEDBACK: Boosting Language Models with Scaled AI Feedback
  9. ICML 2024Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
  10. ICML 2024Unveiling Privacy, Memorization, and Input Curvature Links
  11. ICML 2024VinT-6D: A Large-Scale Object-in-hand Dataset from Vision, Touch and Proprioception
  12. ICML 2024Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
  13. ICML 2024Weighted distance nearest neighbor condensing
  14. ICML 2024What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding
  15. ICML 2024What is Dataset Distillation Learning?
  16. ICML 2024What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
  17. ICML 2024When and How Does In-Distribution Label Help Out-of-Distribution Detection?
  18. ICML 2024Winner-takes-all learners are geometry-aware conditional density estimators

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 查数据集与基准在 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": "dataset-and-benchmarks"}

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数据集与基准论文?
共 5,856 篇,按年份分别是 2023 年 937 篇、2024 年 1,346 篇、2025 年 1,582 篇、2026 年 1,991 篇。
NeurIPS 2026 有多少篇数据集与基准论文?
NeurIPS 2026 有 623 篇数据集与基准论文,上一届是 637 篇。
ICLR 2026 有多少篇数据集与基准论文?
ICLR 2026 有 635 篇数据集与基准论文,上一届是 419 篇。
ICML 2026 有多少篇数据集与基准论文?
ICML 2026 有 275 篇数据集与基准论文,上一届是 189 篇。
CVPR 2026 有多少篇数据集与基准论文?
CVPR 2026 有 458 篇数据集与基准论文,上一届是 337 篇。
哪个会议的数据集与基准论文最多?
NeurIPS,2023–2026 年共 1,935 篇。

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