@SOURADIPCHAKR18: Typical RL algorithms and on-policy distillation methods are blind samplers: they use privileged info to score rollouts…
Summary
This work proposes using privileged information to actively sample rollouts in reinforcement learning, improving on typical blind sampling methods.
View Cached Full Text
Cached at: 05/15/26, 12:45 AM
🚨Typical RL algorithms and on-policy distillation methods are blind samplers: they use privileged info to score rollouts, but not to find them.
We ask: can we use privileged info to actively sample the rollouts RL wishes it can stumble upon with compute?
⤵️ Pedagogical RL https://t.co/c6BcLBDIVv
Similar Articles
@lateinteraction: ICYMI: read the blog on Pedagogical RL Instead of sampling blindly from your LLM, leverage the label used for RLVR! Lea…
Introduces Pedagogical RL, a method that leverages privileged information to guide the sampling of successful trajectories for LLM reasoning, achieving up to 40% relative gains over GRPO and on-policy distillation.
EfficientRollout: System-Aware Self-Speculative Decoding for RL Rollouts
EfficientRollout is a system-aware self-speculative decoding framework that accelerates reinforcement learning rollouts for LLMs by adapting drafters to evolving policies and optimizing speculative decoding regimes, reducing latency by up to 19.6%.
@SOURADIPCHAKR18: We describe early experiments on *pedagogical RL*: A bitter-lesson-pilled paradigm of *training* privileged self-teache…
Introduces pedagogical RL, a paradigm where privileged self-teachers are trained to generate correct and easy-to-follow rollouts, showing it is a relatively easy RL problem.
OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning
OPID proposes an on-policy skill distillation framework that extracts dense hindsight supervision from completed trajectories, combining outcome-based RL with token-level self-distillation to improve language agent training efficiency and performance on multi-turn tasks.
@NielsRogge: One of the hottest terms in AI right now is "On-policy distillation". It is a post-training technique in which a studen…
On-policy distillation is highlighted as a hot post-training technique combining distillation with online RL, now listed on PapersWithCode with 183 citing papers.