主动学习论文趋势 2023–2026

采样策略

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 165 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

主动学习论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023291013658
202413611535
2025977831
202616681141

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

全部主动学习论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 67 篇，第 1 / 2 页

  1. NeurIPS 2026Active Corpus Selection for Training Subgraph Retrievers Using OOD Queries
  2. NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
  3. NeurIPS 2026Active Learning for Conditional Generative Compressed Sensing
  4. NeurIPS 2026Beyond Langevin: Sampling Multimodal Densities using the Witten Laplacian on 1-forms
  5. NeurIPS 2026Do Glimpse Policies See Like Humans? A Behavioral Audit Reveals Dissociated Viewing Priors in Classification-Trained Active Vision
  6. NeurIPS 2026Fixed-Size Active Statistical Inference
  7. NeurIPS 2026Forgetting to Improve: Principled Data Removal in Active Learning
  8. NeurIPS 2026Gumbo: Gumbel Optimized High-Temperature Speculative Sampling
  9. NeurIPS 2026How New Strategies Emerge in RL Post-Training: A Controlled Study
  10. NeurIPS 2026LLM Active Alignment: A Nash Equilibrium Perspective
  11. NeurIPS 2026Online Active Testing: Adaptive Importance Sampling for Unbiased Risk Estimation in Data Streams
  12. NeurIPS 2026Post-ADC Inference: Valid Inference After Active Data Collection
  13. NeurIPS 2026Prediction-Powered Active Testing
  14. NeurIPS 2026Safe Active Learning with Future Viability Guarantees in Time-Series Models
  15. NeurIPS 2026Tactile MNIST: Benchmarking Active Tactile Perception
  16. NeurIPS 2026Towards instance-dependent regret optimality in Episodic MDPs with Posterior Sampling
  17. NeurIPS 2025Active Measurement: Efficient Estimation at Scale
  18. NeurIPS 2025Active Seriation: Efficient Ordering Recovery with Statistical Guarantees
  19. NeurIPS 2025Agnostic Active Learning Is Always Better Than Passive Learning
  20. NeurIPS 2025Balanced Active Inference
  21. NeurIPS 2025Formal Models of Active Learning from Contrastive Examples
  22. NeurIPS 2025Near-Exponential Savings for Population Mean Estimation with Active Learning
  23. NeurIPS 2025Robust Sampling for Active Statistical Inference
  24. NeurIPS 2025Scaling Up Active Testing to Large Language Models
  25. NeurIPS 2025TADA: Improved Diffusion Sampling with Training-free Augmented DynAmics
  26. NeurIPS 2024Active Classification with Few Queries under Misspecification
  27. NeurIPS 2024Active learning of neural population dynamics using two-photon holographic optogenetics
  28. NeurIPS 2024Active Set Ordering
  29. NeurIPS 2024Active, anytime-valid risk controlling prediction sets
  30. NeurIPS 2024Boundary Matters: A Bi-Level Active Finetuning Method
  31. NeurIPS 2024Contextual Active Model Selection
  32. NeurIPS 2024Fairness without Harm: An Influence-Guided Active Sampling Approach
  33. NeurIPS 2024GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
  34. NeurIPS 2024HOPE: Shape Matching Via Aligning Different K-hop Neighbourhoods
  35. NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
  36. NeurIPS 2024Robust Offline Active Learning on Graphs
  37. NeurIPS 2024SEL-BALD: Deep Bayesian Active Learning with Selective Labels
  38. NeurIPS 2024Universal Rates for Active Learning
  39. NeurIPS 2023A Competitive Algorithm for Agnostic Active Learning
  40. NeurIPS 2023Active Bipartite Ranking
  41. NeurIPS 2023Active Learning-Based Species Range Estimation
  42. NeurIPS 2023Active Negative Loss Functions for Learning with Noisy Labels
  43. NeurIPS 2023Active Vision Reinforcement Learning under Limited Visual Observability
  44. NeurIPS 2023Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice
  45. NeurIPS 2023Adaptive Selective Sampling for Online Prediction with Experts
  46. NeurIPS 2023Agnostic Multi-Group Active Learning
  47. NeurIPS 2023Algorithm Selection for Deep Active Learning with Imbalanced Datasets
  48. NeurIPS 2023Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
  49. NeurIPS 2023Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
  50. NeurIPS 2023Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions

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 查主动学习在 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": "active-learning"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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