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 29 篇，第 1 / 1 页

1. ICLR 2026Active Learning for Decision Trees with Provable Guarantees
2. ICLR 2026ActiveCQ: Active Estimation of Causal Quantities
3. ICLR 2026Dynamics-Predictive Sampling for Active RL Finetuning of Large Reasoning Models
4. ICLR 2026PEERING INTO THE UNKNOWN: ACTIVE VIEW SELECTION WITH NEURAL UNCERTAINTY MAPS FOR 3D RECONSTRUCTION
5. ICLR 2026PSP: Prompt-Guided Self-Training Sampling Policy for Active Prompt Learning
6. ICLR 2026TESSAR: Geometry-Aware Active Regression via Dynamic Voronoi Tessellation
7. ICLR 2025Active Learning for Continual Learning: Keeping the Past Alive in the Present
8. ICLR 2025Dual Process Learning: Controlling Use of In-Context vs. In-Weights Strategies with Weight Forgetting
9. ICLR 2025Efficient Active Imitation Learning with Random Network Distillation
10. ICLR 2025Near-optimal Active Regression of Single-Index Models
11. ICLR 2025Provably Accurate Shapley Value Estimation via Leverage Score Sampling
12. ICLR 2025SAVA: Scalable Learning-Agnostic Data Valuation
13. ICLR 2025Uncertainty Herding: One Active Learning Method for All Label Budgets
14. ICLR 2024Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches
15. ICLR 2024IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models
16. ICLR 2024Improved Active Learning via Dependent Leverage Score Sampling
17. ICLR 2024Neural Active Learning Beyond Bandits
18. ICLR 2024One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
19. ICLR 2024Querying Easily Flip-flopped Samples for Deep Active Learning
20. ICLR 2023A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles
21. ICLR 2023Active Image Indexing
22. ICLR 2023Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle
23. ICLR 2023BALTO: fast tensor program optimization with diversity-based active learning
24. ICLR 2023Leveraging Importance Weights in Subset Selection
25. ICLR 2023MCAL: Minimum Cost Human-Machine Active Labeling
26. ICLR 2023Robust Active Distillation
27. ICLR 2023Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing
28. ICLR 2023Scalable Subset Sampling with Neural Conditional Poisson Networks
29. ICLR 2023Selective Annotation Makes Language Models Better Few-Shot Learners

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。