Exploration-Distillation: New RL framework beats DAPO by unlocking aggressive exploration
micahgoldblum · x · 2026-10-13
Researcher Micah Goldblum announced Exploration-Distillation, an RL framework that unlocks aggressive exploration in LLM training and delivers large performance gains over standard algorithms like DAPO.
Key insight: in RLVR the LLM is already pretrained, and the reward supervises only a tiny fraction of its knowledge—a model could forget most of Wikipedia yet still earn high reward. Existing algorithms therefore struggle to let models discover genuinely new things during RL; this framework tackles that head-on.
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