数据集与基准论文趋势 2023–2026

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。

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 2 / 19 页

51. ICML 2026Correct Looks Better: Pairwise Comparisons Reveal Accuracy Rankings
52. ICML 2026Courtroom Analogy: New Perspective on Uncertainty-Aware Classification
53. ICML 2026Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts
54. ICML 2026CriticalKV: Optimizing KV Cache Eviction from an Output Perturbation Perspective
55. ICML 2026CryoACE: An Atom-centric Framework for Accurate and Automated Model Building in Cryo-EM
56. ICML 2026Curating the Future: A Scalable Recipe for Training Open-Ended Forecasters
57. ICML 2026Data Agent: Learning to Select Data via End-to-End Dynamic Optimization
58. ICML 2026DataGuard: A Non-intrusive Dataset Auditing Framework via Differential Information Forensics
59. ICML 2026Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation
60. ICML 2026Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees
61. ICML 2026Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training
62. ICML 2026Decoupling The "What" and "Where" With Polar Coordinate Positional Embedding
63. ICML 2026Deep Trajectory Supervision: Deep Supervision Strikes Back
64. ICML 2026Delegation and Verification under AI
65. ICML 2026Detecting Errors in AI-Generated Annotations: When and Why Semantic Neighbors Help
66. ICML 2026Diffusion Models Preferentially Memorize Prototypical Examples or: Why Does My Diffusion Model Love Slop?
67. ICML 2026Dimensionality Reduction with Point-distributions Similarity Invariant
68. ICML 2026DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
69. ICML 2026Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models
70. ICML 2026Divide and Contrast: Learning Robust Temporal Features without Augmentation
71. ICML 2026DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home
72. ICML 2026Do Activation Verbalization Methods Convey Privileged Information?
73. ICML 2026Does a Hybrid Space-Aware Randomized Defense Improve Empirical and Certified Adversarial Robustness?
74. ICML 2026DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation
75. ICML 2026DualCOIL: Offline Imitation Learning from Contrasting Demonstrations
76. ICML 2026Dynamic Linear Attention
77. ICML 2026Dynamic Multimodal Evaluation via Knowledge-Enhanced Benchmark Evolution
78. ICML 2026DynaSchedBench: Calibrated Dynamic Scheduling Benchmarks and Observability Paradox in LLM-based Scheduling Agents
79. ICML 2026EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation and Diagnostic Analyses of EEG Foundation Models
80. ICML 2026Efficient Multi-modal Dataset Distillation via Analytic Parameter Matching
81. ICML 2026Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets
82. ICML 2026Empirical Gaussian Processes
83. ICML 2026Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion Models
84. ICML 2026Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions
85. ICML 2026Evaluating Language Models in Realistic Conversational Contexts
86. ICML 2026Evaluating Object-Centric Models beyond Object Discovery
87. ICML 2026Expanding the AI Evaluation Toolbox with Statistical Models
88. ICML 2026Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift
89. ICML 2026Exploring 3D Dataset Pruning
90. ICML 2026FairJudge : An Adaptive, Debiased, and Consistent LLM-as-a-Judge
91. ICML 2026Falling Trees: A Model Class for Interpretable Risk Prioritization
92. ICML 2026Fast k-means Seeding Under The Manifold Hypothesis
93. ICML 2026Faults in Our Formal Benchmarking: Dataset Defects and Evaluation Failures in Lean Theorem Proving
94. ICML 2026FedARC: Anchor-Guided Residual Compensation for Data and Model Heterogeneous Federated Learning
95. ICML 2026Federated Data and Feature Selection by Generalized CUR Decomposition
96. ICML 2026Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
97. ICML 2026Fine-Tune Once, Reuse Across Models: Bayesian Task-Update Factors and Approximations
98. ICML 2026FiX: Introducing Fine-grained Forget Gate into Softmax Attention
99. ICML 2026Fixed Aggregation Features Can Rival GNNs
100. ICML 2026FLIP2: Expanding Protein Fitness Landscape Benchmarks for Real-World Machine Learning Applications

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。