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 948 篇，第 17 / 19 页
- ICML 2023Bootstrap in High Dimension with Low Computation
- ICML 2023Can Neural Network Memorization Be Localized?
- ICML 2023Change is Hard: A Closer Look at Subpopulation Shift
- ICML 2023Cluster Explanation via Polyhedral Descriptions
- ICML 2023ClusterFuG: Clustering Fully connected Graphs by Multicut
- ICML 2023Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation
- ICML 2023Consistency of Multiple Kernel Clustering
- ICML 2023Contextual Combinatorial Bandits with Probabilistically Triggered Arms
- ICML 2023Contextual Reliability: When Different Features Matter in Different Contexts
- ICML 2023Cross-Modal Fine-Tuning: Align then Refine
- ICML 2023CrossSplit: Mitigating Label Noise Memorization through Data Splitting
- ICML 2023Data Feedback Loops: Model-driven Amplification of Dataset Biases
- ICML 2023Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value
- ICML 2023Dataset Distillation with Convexified Implicit Gradients
- ICML 2023Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
- ICML 2023Decoding Layer Saliency in Language Transformers
- ICML 2023Dink-Net: Neural Clustering on Large Graphs
- ICML 2023Directed Chain Generative Adversarial Networks
- ICML 2023Discrete Key-Value Bottleneck
- ICML 2023Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape
- ICML 2023Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian
- ICML 2023Emergence of Sparse Representations from Noise
- ICML 2023Estimating Joint Treatment Effects by Combining Multiple Experiments
- ICML 2023Evaluating Unsupervised Denoising Requires Unsupervised Metrics
- ICML 2023Explainability as statistical inference
- ICML 2023Exploring the Benefits of Training Expert Language Models over Instruction Tuning
- ICML 2023Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks
- ICML 2023Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms
- ICML 2023Fair and Optimal Classification via Post-Processing
- ICML 2023Fast Excess Risk Rates via Offset Rademacher Complexity
- ICML 2023Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective
- ICML 2023Finding Generalization Measures by Contrasting Signal and Noise
- ICML 2023Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs
- ICML 2023Fisher Information Embedding for Node and Graph Learning
- ICML 2023From Hypergraph Energy Functions to Hypergraph Neural Networks
- ICML 2023Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods
- ICML 2023Generalized Implicit Follow-The-Regularized-Leader
- ICML 2023Geometric Autoencoders - What You See is What You Decode
- 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
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。