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

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,346 篇，第 15 / 27 页

  1. ICML 2024Harmonizing Generalization and Personalization in Federated Prompt Learning
  2. ICML 2024Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis
  3. ICML 2024Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning
  4. ICML 2024Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity
  5. ICML 2024How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model
  6. ICML 2024How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
  7. ICML 2024How Spurious Features are Memorized: Precise Analysis for Random and NTK Features
  8. ICML 2024How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
  9. ICML 2024How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis
  10. ICML 2024Hybrid Reinforcement Learning from Offline Observation Alone
  11. ICML 2024Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
  12. ICML 2024Imitation Learning in Discounted Linear MDPs without exploration assumptions
  13. ICML 2024Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD
  14. ICML 2024Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials
  15. ICML 2024Improved Operator Learning by Orthogonal Attention
  16. ICML 2024Improving Antibody Humanness Prediction using Patent Data
  17. ICML 2024Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation
  18. ICML 2024Improving Sharpness-Aware Minimization by Lookahead
  19. ICML 2024In-Context Language Learning: Architectures and Algorithms
  20. ICML 2024In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
  21. ICML 2024Incremental Topological Ordering and Cycle Detection with Predictions
  22. ICML 2024InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks
  23. ICML 2024Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks
  24. ICML 2024Initial Guessing Bias: How Untrained Networks Favor Some Classes
  25. ICML 2024Integrating Global Context Contrast and Local Sensitivity for Blind Image Quality Assessment
  26. ICML 2024InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning
  27. ICML 2024Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification
  28. ICML 2024Interpreting and Improving Diffusion Models from an Optimization Perspective
  29. ICML 2024Interpreting and Improving Large Language Models in Arithmetic Calculation
  30. ICML 2024Junk DNA Hypothesis: Pruning Small Pre-Trained Weights $\textit{Irreversibly}$ and $\textit{Monotonically}$ Impairs ``Difficult" Downstream Tasks in LLMs
  31. ICML 2024Kepler codebook
  32. ICML 2024KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations
  33. ICML 2024Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
  34. ICML 2024Language Models as Science Tutors
  35. ICML 2024Large Scale Dataset Distillation with Domain Shift
  36. ICML 2024Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping
  37. ICML 2024LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies
  38. ICML 2024Learning 1-Bit Tiny Object Detector with Discriminative Feature Refinement
  39. ICML 2024Learning and Forgetting Unsafe Examples in Large Language Models
  40. ICML 2024Learning Decision Policies with Instrumental Variables through Double Machine Learning
  41. ICML 2024Learning Decision Trees and Forests with Algorithmic Recourse
  42. ICML 2024Learning from Integral Losses in Physics Informed Neural Networks
  43. ICML 2024Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
  44. ICML 2024Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds
  45. ICML 2024Learning Mixtures of Gaussian Processes through Random Projection
  46. ICML 2024Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series
  47. ICML 2024Learning the Target Network in Function Space
  48. ICML 2024Learning to Compile Programs to Neural Networks
  49. ICML 2024Learning to Remove Cuts in Integer Linear Programming
  50. ICML 2024Learning Universal Predictors

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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