主动学习论文趋势 2023–2026

主要结论

• 主动学习论文从 2023 年的 58 篇降到 2026 年的 41 篇，热度在回落。
• NeurIPS 是发主动学习论文最多的会议，2023–2026 年共 67 篇，占四个会议总量的 41%。
• 交叉方向里涨得最快的是三维视觉：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 6 篇。
• 在「以数据为中心 AI」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的合成数据生成是 1.3 倍，主动学习是 0.7 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 2026Active Corpus Selection for Training Subgraph Retrievers Using OOD Queries
• ICML 2026Active Regression for Single-Index Models with Unknown Link Functions
• ICLR 2026ActiveCQ: Active Estimation of Causal Quantities
• CVPR 2026Active Inference for Micro-Gesture Recognition EFE-Guided Temporal Sampling and Adaptive
• NeurIPS 2025Active Measurement: Efficient Estimation at Scale
• ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
• ICLR 2025Dual Process Learning: Controlling Use of In-Context vs. In-Weights Strategies with Weight Forgetting
• CVPR 2025Active Hyperspectral Imaging Using an Event Camera
• NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
• ICML 2024Active Statistical Inference
• ICLR 2024Improved Active Learning via Dependent Leverage Score Sampling
• CVPR 2024NARUTO: Neural Active Reconstruction from Uncertain Target Observations
• NeurIPS 2023A Competitive Algorithm for Agnostic Active Learning
• ICML 2023A Two-Stage Active Learning Algorithm for k-Nearest Neighbors
• ICLR 2023A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles
• CVPR 2023Re-Thinking Federated Active Learning Based on Inter-Class Diversity
• NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
• ICML 2026Active Timepoint Selection for Learning Measure-Valued Trajectories
• ICLR 2026TESSAR: Geometry-Aware Active Regression via Dynamic Voronoi Tessellation
• CVPR 2026EventHub Data Factory for Generalizable Event-Based Stereo Networks without Active

全部主动学习论文

共 31 篇，第 1 / 1 页

1. CVPR 2025Active Data Curation Effectively Distills Large-Scale Multimodal Models
2. CVPR 2025Active Hyperspectral Imaging Using an Event Camera
3. CVPR 2025EnliveningGS: Active Locomotion of 3DGS
4. CVPR 2025Learning Extremely High Density Crowds as Active Matters
5. CVPR 2025RaSS: Improving Denoising Diffusion Samplers with Reinforced Active Sampling Scheduler
6. CVPR 2025Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach
7. CVPR 2025Towards Cost-Effective Learning: A Synergy of Semi-Supervised and Active Learning
8. CVPR 2025Uncertainty Meets Diversity: A Comprehensive Active Learning Framework for Indoor 3D Object Detection
9. ICLR 2025Active Learning for Continual Learning: Keeping the Past Alive in the Present
10. ICLR 2025Dual Process Learning: Controlling Use of In-Context vs. In-Weights Strategies with Weight Forgetting
11. ICLR 2025Efficient Active Imitation Learning with Random Network Distillation
12. ICLR 2025Near-optimal Active Regression of Single-Index Models
13. ICLR 2025Provably Accurate Shapley Value Estimation via Leverage Score Sampling
14. ICLR 2025SAVA: Scalable Learning-Agnostic Data Valuation
15. ICLR 2025Uncertainty Herding: One Active Learning Method for All Label Budgets
16. ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
17. ICML 2025Active Treatment Effect Estimation via Limited Samples
18. ICML 2025AutoAL: Automated Active Learning with Differentiable Query Strategy Search
19. ICML 2025Efficient Heterogeneity-Aware Federated Active Data Selection
20. ICML 2025Importance Sampling for Nonlinear Models
21. ICML 2025Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
22. ICML 2025On the Benefits of Active Data Collection in Operator Learning
23. NeurIPS 2025Active Measurement: Efficient Estimation at Scale
24. NeurIPS 2025Active Seriation: Efficient Ordering Recovery with Statistical Guarantees
25. NeurIPS 2025Agnostic Active Learning Is Always Better Than Passive Learning
26. NeurIPS 2025Balanced Active Inference
27. NeurIPS 2025Formal Models of Active Learning from Contrastive Examples
28. NeurIPS 2025Near-Exponential Savings for Population Mean Estimation with Active Learning
29. NeurIPS 2025Robust Sampling for Active Statistical Inference
30. NeurIPS 2025Scaling Up Active Testing to Large Language Models
31. NeurIPS 2025TADA: Improved Diffusion Sampling with Training-free Augmented DynAmics

常见问题

2023–2026 年四大会议一共有多少篇主动学习论文？

共 165 篇，按年份分别是 2023 年 58 篇、2024 年 35 篇、2025 年 31 篇、2026 年 41 篇。

NeurIPS 2026 有多少篇主动学习论文？

NeurIPS 2026 有 16 篇主动学习论文，上一届是 9 篇。

ICLR 2026 有多少篇主动学习论文？

ICLR 2026 有 6 篇主动学习论文，上一届是 7 篇。

ICML 2026 有多少篇主动学习论文？

ICML 2026 有 8 篇主动学习论文，上一届是 7 篇。

CVPR 2026 有多少篇主动学习论文？

CVPR 2026 有 11 篇主动学习论文，上一届是 8 篇。

哪个会议的主动学习论文最多？

NeurIPS，2023–2026 年共 67 篇。