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Mu-Yang Li

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#machine learning Preprint Sep 2026

PR-OPD: Privileged Representation On-policy Self-Distillation for Agentic Reinforcement Learning

Language-model agents are usually trained by reinforcement learning from one reward per episode, and privileged self-distillation enriches it by letting the same policy, given a skill, teach its skill-free self through token probabilities. However, we identify two phenomena that question this channel. Invisible Advanta...

Mu-Yang Li, Jie Yang, Zheng-Yu Fang et al. · 0 citations
Jul 2026

Early Stopping Without Validation Data in Weakly Supervised Learning.

Label Wave is proposed, which does not require validation data for selecting the desired model across various weakly supervised learning paradigms, including learning with noisy labels (LNL), positive-unlabeled learning, and unlabeled-unlabeled learning.

Suqin Yuan, Muyang Li, Lei Feng et al. · 0 citations

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