Active Learning

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Overview

Active learning studies how to choose data or queries so models can learn effectively with fewer labels, measurements, or experiments. Common approaches include uncertainty sampling, diversity and coreset selection, Bayesian information gain, batch strategies, and cost-aware or human-in-the-loop querying; scientific applications also use Gaussian processes, multi-fidelity models, and physics-based acquisition to guide simulations and laboratory work. Work spans image and language benchmarks, medical annotation, robotics, and scientific discovery, with newer methods using foundation-model representations and adapting selection to class imbalance, domain shift, or label noise. A central open tension is that no acquisition strategy wins everywhere: gains depend on the task, budget, model and data, and random sampling can match or outperform sophisticated methods, making realistic evaluations and strong baselines essential.

Latest papers

CardsList

296 papers39 papers in the last four weeks, up 22% on the four weeks before. 0.2% of all new papers.

  1. CAAL: Contextual Bandits based Online Hand-Craft Active Learning Strategy Selection

    Jun 6, 2026Shao-An Yin, Jiacong Li, Tianpei Xie +3Active LearningContextual Bandits

    Department of Electrical and Computer Engineering, University of Minnesota, Twin Cities, USA · Jiacong Li, Tianpei Xie, Cecile Levasseur, and Wojciech Kowalinski are with Amazon.

  2. HARP: Efficient Data Selection for Finetuning Large Language Models

    Jun 5, 2026Ning Wang, Zhengxin Zhang, Maosen Tang +3LLM Fine-TuningActive Learning

    Cornell University · The Hong Kong University of Science and Technology

  3. Activation-Based Active Learning for In-Context Learning: Challenges and Insights

    Jun 3, 2026Yaseen M. Osman, Geoff V. Merrett, Stuart E. MiddletonIn-Context Example SelectionActive Learning

    School of Electronics and Computer Science, University of Southampton, United Kingdom

  4. ALINC: Active Learning for Inductive Node Classification via Graph Sampling

    Jun 3, 2026Pascal Plettenberg, Denis Huseljic, André Alcalde +2Active LearningNode Classification

    Intelligent Embedded Systems, University of Kassel, 34121 Kassel, Germany · CELUS GmbH, 80339 Munich, Germany · GAIN Group, Institute of Data Science, University of Greifswald, 17489 Greifswald, Germany

  5. Smart Picks in the Dark: Towards Efficient RLVR for Reasoning via Tracing Metacognitive Pivots

    Jun 3, 2026Guangcheng Zhu, Shenzhi Yang, Haobo Wang +7Uncertainty QuantificationRL for Language Model Reasoning

    Zhejiang University · Ant Group

  6. Stein Kernelized Molecular Dynamics for Active Learning of Interatomic Potentials

    Jun 2, 2026Joanna Zou, Fraser Birks, Dallas Foster +1Machine Learning Interatomic PotentialsActive Learning

    Center for Computational Science & Engineering, Schwarzman College of Computing, MIT · Warwick Centre for Predictive Modelling, School of Engineering, University of Warwick · NVIDIA

  7. Finding Needles in the Haystack: Transductive Active Labeling in Ecology

    Jun 2, 2026Rupa Kurinchi-Vendhan, Sara BeeryLong-Tailed ClassificationActive Learning

    Massachusetts Institute of Technology, Cambridge MA 02139, USA

  8. FACT: A Simple and Efficient Framework for Active Finetuning

    Jun 1, 2026Wenshuai Xu, You Song, Yuzhuo Cui +3Active LearningImage Classification

  9. Query-Limited Community Recovery in Stochastic Block Models

    Jun 1, 2026Sabyasachi Basu, Manuj Mukherjee, Lutz Oettershagen +1Active LearningAdaptive Sampling

    1Microsoft Research, India · 2Indraprastha Institute of Information Technology, India · University of Liverpool, United Kingdom +1

  10. Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance

    May 30, 2026Jiancheng Zhang, Meiqing Li, Qi Zhang +1Class-Imbalanced LearningActive Learning

    University of California, Riverside · 2Carnegie Mellon University · 3Worcester Polytechnic Institute

  11. Distributed GNEP Algorithms without Multiplier Sharing and Applications to Multi-Robot Coordination and Contextual Bandit-Based Active Learning

    May 30, 2026Shao-An YinGame TheoryDistributed Optimization

    UNIVERSITY OF MINNESOTA

  12. Active Timepoint Selection for Learning Measure-Valued Trajectories

    May 28, 2026Nicolas Huynh, Mihaela van der SchaarActive Learning

    DAMTP, University of Cambridge

  13. Active Continual Learning with Metaplastic Binary Bayesian Neural Networks

    May 28, 2026Kellian Cottart, Théo Ballet, Djohan Bonnet +1Bayesian Neural NetworksBinary Neural Networks

    Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies, Palaiseau, France · Forschungszentrum Jülich, Germany

  14. User-Aware Active Knowledge Acquisition for Emotional Support Dialogue

    May 28, 2026Mufan Xu, Kehai Chen, Jiahao Hu +4Emotional Support ConversationActive Learning

    Harbin Institute of Technology, China · Baidu Inc., Beijing, China

  15. MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality

    May 28, 2026Yujin Park, Haejun Chung, Ikbeom JangLearning to RankActive Learning

    Hanyang University Seoul, Republic of Korea · Hankuk University of Foreign Studies Yongin, Republic of Korea

  16. Theoretical Foundations and Effective Algorithms for Policy-Aware Simulator Learning

    May 27, 2026Christoph Dann, Yishay Mansour, Mehryar MohriSim-to-Real TransferActive Learning

    Google Research · Tel Aviv University and Google Research · Google Research and Courant Institute of Mathematical Sciences

  17. Active Query Synthesis for Preference Learning

    May 25, 2026Namrata Nadagouda, Nauman Ahad, Maegan Tucker +1Pairwise Preference LearningActive Learning

    Georgia Institute of Technology · Gauss Labs

  18. Adaptive Graph Refinement and Label Propagation with LLMs for Cost-Effective Entity Resolution

    May 25, 2026Hongtao Wang, Renchi Yang, Haoran Zheng +1Graph Structure LearningEntity Resolution

    Hong Kong Baptist University · Hong Kong, China · Zhejiang University +1

  19. Large Language Model Selection with Limited Annotations

    May 24, 2026Yavuz Durmazkeser, Patrik Okanovic, Andreas Kirsch +2Model SelectionLLM Evaluation

    TU Delft · ETH Zurich

  20. Active Learning for Stochastic Contextual Linear Bandits

    May 24, 2026Emma Brunskill, Ishani Karmarkar, Zhaoqi LiActive LearningAdaptive Sampling

    Stanford University

  21. AvAtar: Learning to Align via Active Optimal Transport

    May 23, 2026Qi Yu, Ruizhong Qiu, Zhichen Zeng +3Active LearningOptimal Transport

    University of Illinois Urbana-Champaign · University of Florida · 3Arizona State University

  22. Balancing Uncertainty and Diversity of Samples: Leveraging Diversity of Least, High Confidence Samples for Effective Active Learning

    May 21, 2026Vipul Arya, S. H. Shabbeer Basha, Srikrishna U N +2Active LearningUncertainty Sampling

    School of Computer Science and Engineering, RV University, Bengaluru, Karnataka-560059, India · School of Engineering & Technology, Vidyashilp University, Bangalore, India · Shiv Nadar Institution of Eminence, Delhi NCR

  23. Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale

    May 20, 2026Ralph Bulanadi, Jefferey Baxter, Arpan Biswas +5Pairwise Preference LearningDeep Kernel Learning

    Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA · University of Tennessee-Oak Ridge Innovation Institute, University of Tennessee, Knoxville, TN 37996, USA · Department of Material Science and Engineering, School of Materials and Chemical Technology, Institute of Science Tokyo, Yokohama, 226-8502, Japan +3

  24. Data-Efficient Neural Operator Training via Physics-Based Active Learning

    May 20, 2026Alicja Polanska, Lorenzo Zanisi, Vignesh Gopakumar +1Active LearningPhysics-Informed ML

    University College London · United Kingdom Atomic Energy Authority

  25. Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations

    May 20, 2026Kin Whye Chew, Jingxian WangMeta-LearningActive Learning

    Department of Computer Science National University of Singapore Singapore, S119077

  26. A Mutual Information Lower Bound for Multimodal Regression Active Learning

    May 14, 2026Leonardo Ferreira Guilhoto, Akshat Kaushal, Paris PerdikarisMixture Density NetworksActive Learning

    Graduate Group on Applied Mathematics & Computational Science · Department of Computer and Information Science University of Pennsylvania Philadelphia, PA 19104 · Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania Philadelphia, PA 19104

  27. Are Candidate Models Really Needed for Active Learning?

    May 14, 2026Harshini Mridula Mohan, Maanya Manjunath, Vipul Arya +2Active Learning

    a SoCSE, RV University, Bengaluru, India. · b School of Engineering and Technology, Vidyashilp University, Bengaluru, India. · c Dataplex Inc., USA.

  28. AQKA: Active Quantum Kernel Acquisition Under a Shot Budget

    May 14, 2026Jian Xu, Chao Li, Delu Zeng +2Kernel RegressionActive Learning

    1RIKEN iTHEMS · 2RIKEN AIP · 3South China University of Technology +1

  29. Active Learners as Efficient PRP Rerankers

    May 14, 2026Jeremías Figueiredo Paschmann, Juan Kaplan, Francisco Nattero +3Pairwise Preference LearningPairwise Comparison

    ELIAS Lab, Departamento de Ingeniería, Universidad de San Andrés

  30. Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs

    May 13, 2026Eszter Varga-Umbrich, Zachary Weller-Davies, Paul Duckworth +3Machine Learning Interatomic PotentialsDistribution Shift

    InstaDeep, UK · Department of Engineering, University of Cambridge, Cambridge, UK