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cs.LG2026
Latent-MOPD: Latent Multi-Teacher On-Policy Distillation
Zhengyu Fang, Seoyeon Hong, Jie Yang +4
On-policy distillation (OPD) trains a student on the responses it generates. Existing LLM multi-teacher OPD transfers what specialists predict through their output distributions. W…
cs.LG2026
PR-OPD: Privileged Representation On-policy Self-Distillation for Agentic Reinforcement Learning
Muyang Li, Jie Yang, Zhengyu Fang +5
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 sk…