Learning Using Privileged Information

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Overview

The field studies how extra information available during training—such as future observations, detailed labels, other sensor modalities, or expert feedback—can help a model that will not receive it at deployment. Common approaches include teacher–student distillation, privileged-feature SVMs, representation learning, and reinforcement learning with guided or hindsight-informed rollouts. These methods are used in settings from robotics and autonomous driving to medical imaging, vision-language models, and reasoning agents. The central tension is that richer guidance can improve learning, but may also teach shortcuts or bias the student toward evidence it cannot access, so useful supervision must be relevant, reliable, and transferable to ordinary inputs.

Latest papers

CardsList

70 papers14 papers in the last four weeks, up 27% on the four weeks before. 0.1% of all new papers.

  1. ππ-Play: Multi-Agent Self-Play via Privileged Self-Distillation without External Data

    Apr 15, 2026Yaocheng Zhang, Yuanheng Zhu, Wenyue Chong +7Self-Play RLSelf-Evolving Agents

    Institute of Automation, Chinese Academy of Sciences · School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences +1

  2. PriPG-RL: Privileged Planner-Guided Reinforcement Learning for Partially Observable Systems with Anytime-Feasible MPC

    Apr 9, 2026Mohsen Amiri, Mohsen Amiri, Ali Beikmohammadi +2Partially Observable RLLearning Using Privileged Information

    The authors are with the Department of Computer and System Science, Stockholm University, 11419 Stockholm, Sweden · The authors are with the School of Mechanical and Material Engineering, Washington State University, Pullman, WA 99164, USA

  3. Maximizing T2-Only Prostate Cancer Localization from Expected Diffusion Weighted Imaging

    Apr 1, 2026Weixi Yi, Yipei Wang, Wen Yan +10Medical Image LocalizationMagnetic Resonance Imaging

    the UCL Hawkes Institute and the Department of Medical Physics and Biomedical Engineering, University College London, London, UK · the Centre for Medical Imaging, University College London, London, UK · the Division of Surgery & Interventional Science, University College London, London, UK +2

  4. Longitudinal Risk Prediction in Mammography with Privileged History Distillation

    Mar 16, 2026Banafsheh Karimian, Soufiane Belharbi, Alexis Guichemerre +3Breast CancerMedical Imaging

    LIVIA, Dept. of Systems Engineering, ETS Montreal, Canada · Goodman Cancer Institute, Dept. of Oncology, McGill University, Canada

  5. Efficient Real-World Autonomous Racing via Attenuated Residual Policy Optimization

    Mar 13, 2026Raphael Trumpp, Denis Hoornaert, Mirco Theile +1Residual Policy LearningAutonomous Racing

    Technical University of Munich, Munich, Germany

  6. PTLD: Sim-to-real Privileged Tactile Latent Distillation for Dexterous Manipulation

    Mar 4, 2026Rosy Chen, Mustafa Mukadam, Michael Kaess +4Dexterous ManipulationSim-to-Real Transfer

    Carnegie Mellon University · University of Washington · FAIR at Meta +1

  7. OncoVision: Integrating Mammography and Clinical Data through Attention-Driven Multimodal AI for Enhanced Breast Cancer Diagnosis

    Nov 24, 2025Istiak Ahmed, Galib Ahmed, K. Shahriar Sanjid +10Breast CancerMedical Image Segmentation

    Department Electrical and Computer Engineering, North South University, Dhaka, 1229, Bangladesh. · Big-Matrix Lab, North South University, Dhaka, 1229, Bangladesh. · Department of Mathematics and Physics, North South University, Dhaka, 1229, Bangladesh. +7

  8. To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning

    Oct 3, 2025Yuda Song, Dhruv Rohatgi, Aarti Singh +1Partially Observable RLLearning Using Privileged Information

    Carnegie Mellon University · Massachusetts Institute of Technology · Aurora Innovation

  9. From My View to Yours: Learning Egocentric Cues from Exocentric Video using Privileged Egocentric Supervision

    Jan 10, 2025Dominick Reilly, Manish Kumar Govind, Le Xue +1Video UnderstandingVLM Adaptation

    University of North Carolina at Charlotte · Elorian AI

  10. PA-LOCO: Learning Perturbation-Adaptive Locomotion for Quadruped Robots

    Jul 5, 2024Zhiyuan Xiao, Xinyu Zhang, Xiang Zhou +1RL for Legged LocomotionQuadruped Locomotion

    School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen 518107, P.R. China.