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On-Policy Distillation Works Better Without the Teacher

This story is from 2026-09-01. It is preserved in the archive; the latest stories are on the live feed.

On-policy distillation has become one of the standard recipes for training small reasoning models. If outcome-level reinforcement learning with verifiable rewards gives you sparse feedback only at the end of a long chain of thought, on-policy distillation offers dense token-level advantages. The st…

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  1. 2026-09-01 17:00 · DEV Community — Machine Learning
    On-Policy Distillation Works Better Without the Teacher

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