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 1,346 篇，第 17 / 27 页
- ICML 2024Overcoming Saturation in Density Ratio Estimation by Iterated Regularization
- ICML 2024Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
- ICML 2024PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
- ICML 2024Perturb-and-Project: Differentially Private Similarities and Marginals
- ICML 2024Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach
- ICML 2024Plug-and-Play image restoration with Stochastic deNOising REgularization
- ICML 2024PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels
- ICML 2024Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction
- ICML 2024Position: A Roadmap to Pluralistic Alignment
- ICML 2024Position: A Safe Harbor for AI Evaluation and Red Teaming
- ICML 2024Position: AI/ML Influencers Have a Place in the Academic Process
- ICML 2024Position: Amazing Things Come From Having Many Good Models
- ICML 2024Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
- ICML 2024Position: Benchmarking is Limited in Reinforcement Learning Research
- ICML 2024Position: Is machine learning good or bad for the natural sciences?
- ICML 2024Position: Measure Dataset Diversity, Don't Just Claim It
- ICML 2024Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
- ICML 2024Position: Topological Deep Learning is the New Frontier for Relational Learning
- ICML 2024Position: TrustLLM: Trustworthiness in Large Language Models
- ICML 2024Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
- ICML 2024Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
- ICML 2024Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
- ICML 2024Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
- ICML 2024Prodigy: An Expeditiously Adaptive Parameter-Free Learner
- ICML 2024Provable Contrastive Continual Learning
- ICML 2024Provably Scalable Black-Box Variational Inference with Structured Variational Families
- ICML 2024PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency
- ICML 2024Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
- ICML 2024QuIP$\#$: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
- ICML 2024ReconBoost: Boosting Can Achieve Modality Reconcilement
- ICML 2024Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations
- ICML 2024Regularized Q-learning through Robust Averaging
- ICML 2024Residual Quantization with Implicit Neural Codebooks
- ICML 2024Rethinking Decision Transformer via Hierarchical Reinforcement Learning
- ICML 2024Rethinking Generative Large Language Model Evaluation for Semantic Comprehension
- ICML 2024Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
- ICML 2024Rethinking the Flat Minima Searching in Federated Learning
- ICML 2024Rich-Observation Reinforcement Learning with Continuous Latent Dynamics
- ICML 2024RLVF: Learning from Verbal Feedback without Overgeneralization
- ICML 2024Robust Learning-Augmented Dictionaries
- ICML 2024Robust Universal Adversarial Perturbations
- ICML 2024Rolling Diffusion Models
- ICML 2024Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks
- ICML 2024S3O: A Dual-Phase Approach for Reconstructing Dynamic Shape and Skeleton of Articulated Objects from Single Monocular Video
- ICML 2024Saliency strikes back: How filtering out high frequencies improves white-box explanations
- ICML 2024SAPG: Split and Aggregate Policy Gradients
- ICML 2024Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
- ICML 2024Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation
- ICML 2024Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
- ICML 2024SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching
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。