Research · Thursday 1 October 2026 · story 15
Paper studies scaling in same-family on-policy distillation
Hugging Face reports a paper on on-policy distillation found an early useful-transfer phase where held-out accuracy rose about linearly with reverse KL from student initialization. The paper says each observed weak-to-strong setup let the student's peak gold score top the teacher's own.
Why it matters. For AI agent builders, the results suggest a smaller RL expert can supervise a larger model, and teacher score alone does not define supervision value.
Read the original at huggingface.co