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
- 数据集与基准论文从 2023 年的 937 篇增长到 2026 年的 1,991 篇，三年间扩大到约 2.1 倍。
- NeurIPS 是发数据集与基准论文最多的会议，2023–2026 年共 1,935 篇，占四个会议总量的 33%。
- 交叉方向里涨得最快的是AI 智能体：同时属于两个主题的论文从 2023 年的 8 篇增至 2026 年的 194 篇。
- 在「效率与系统」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的硬件协同是 4.4 倍，数据集与基准是 2.1 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 227 | 162 | 166 | 382 | 937 |
| 2024 | 448 | 216 | 318 | 364 | 1,346 |
| 2025 | 637 | 419 | 189 | 337 | 1,582 |
| 2026 | 623 | 635 | 275 | 458 | 1,991 |
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
- NeurIPS 2026A Surrogate Perspective on Convergence of Fixed-Target DQN
- ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
- ICLR 2026**TandemFoilSet**: Datasets for Flow Field Prediction of Tandem-Airfoil Through the Reuse of Single Airfoils
- CVPR 20264DEquine Disentangling Motion and Appearance for 4D Equine Reconstruction from
- NeurIPS 2025A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design
- ICML 2025Active Evaluation Acquisition for Efficient LLM Benchmarking
- ICLR 2025$F^3Set$: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
- CVPR 20253D-GRAND: A Million-Scale Dataset for 3D-LLMs with Better Grounding and Less Hallucination
- NeurIPS 2024A Benchmark Dataset for Event-Guided Human Pose Estimation and Tracking in Extreme Conditions
- ICML 2024A connection between Tempering and Entropic Mirror Descent
- ICLR 2024A Benchmark Study on Calibration
- CVPR 2024Data Valuation and Detections in Federated Learning
- NeurIPS 2023$\mathbf{\mathbb{E}^{FWI}}$: Multiparameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties
- ICML 2023A Picture of the Space of Typical Learnable Tasks
- ICLR 2023$\Lambda$-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells
- CVPR 2023A Bag-of-Prototypes Representation for Dataset-Level Applications
- NeurIPS 2026A Theoretical Bridge Between Long-Tailed Recognition and Continual Learning
- ICML 2026A Semantically Consistent Dataset for Data-Efficient Query-Based Universal Sound Separation
- ICLR 2026A Fictional Q&A Dataset for Studying Memorization and Knowledge Acquisition
- CVPR 2026Advancing Cancer Prognosis with Hierarchical Fusion of Genomic Proteomic and
全部数据集与基准论文
共 937 篇，第 13 / 19 页
- ICML 2023GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
- ICML 2023Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement
- ICML 2023Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs
- ICML 2023High Probability Convergence of Stochastic Gradient Methods
- ICML 2023High-dimensional Clustering onto Hamiltonian Cycle
- ICML 2023Horizon-free Learning for Markov Decision Processes and Games: Stochastically Bounded Rewards and Improved Bounds
- ICML 2023How Does Information Bottleneck Help Deep Learning?
- ICML 2023Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning
- ICML 2023Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
- ICML 2023Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples
- ICML 2023Improving Fair Training under Correlation Shifts
- ICML 2023In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation
- ICML 2023InfoOT: Information Maximizing Optimal Transport
- ICML 2023Input uncertainty propagation through trained neural networks
- ICML 2023Investigating the Role of Model-Based Learning in Exploration and Transfer
- ICML 2023Iterative Approximate Cross-Validation
- ICML 2023JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift
- ICML 2023Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity
- ICML 2023Learnability and Algorithm for Continual Learning
- ICML 2023Learning Dense Correspondences between Photos and Sketches
- ICML 2023Learning Dynamic Query Combinations for Transformer-based Object Detection and Segmentation
- ICML 2023Learning GFlowNets From Partial Episodes For Improved Convergence And Stability
- ICML 2023Learning Mixtures of Markov Chains and MDPs
- ICML 2023Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation
- ICML 2023Learning Prescriptive ReLU Networks
- ICML 2023Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning
- ICML 2023Learning to Boost Training by Periodic Nowcasting Near Future Weights
- ICML 2023LegendreTron: Uprising Proper Multiclass Loss Learning
- ICML 2023Linear CNNs Discover the Statistical Structure of the Dataset Using Only the Most Dominant Frequencies
- ICML 2023Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels
- ICML 2023MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
- ICML 2023Margin-based Neural Network Watermarking
- ICML 2023Measuring the Impact of Programming Language Distribution
- ICML 2023Mechanistic Mode Connectivity
- ICML 2023Mu$^2$SLAM: Multitask, Multilingual Speech and Language Models
- ICML 2023Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries
- ICML 2023Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA
- ICML 2023Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data
- ICML 2023New metrics and search algorithms for weighted causal DAGs
- ICML 2023On the Connection Between MPNN and Graph Transformer
- ICML 2023On the Convergence of SARSA with Linear Function Approximation
- ICML 2023On the Forward Invariance of Neural ODEs
- ICML 2023On the Identifiability and Estimation of Causal Location-Scale Noise Models
- ICML 2023On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits
- ICML 2023On the Statistical Benefits of Temporal Difference Learning
- ICML 2023One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training
- ICML 2023Optimal Arms Identification with Knapsacks
- ICML 2023Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning
- ICML 2023PAC-Bayesian Offline Contextual Bandits With Guarantees
- ICML 2023Predicting Ordinary Differential Equations with Transformers
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"}
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。