Rethinking Privileged Information in On-Policy Self-Distillation
On-policy self-distillation (OPSD) trains a student on its own responses using token-level supervision from the same model conditioned on privileged reference information. We investigate whether performance gains from OPSD show that the student learned the information in the reference or instead reflect recovery of reasoning behavior already present in the base model. We perform OPSD experiments on science and mathematics datasets using Qwen3 models ranging from 1.7B to 8B. Our analysis framework separates the supervision induced by the reference from the supervision provided by the teacher without the reference and measures how each aligns with changes in the student's predictions. The c...
| Authors | Samyak Shrestha, Alexander Tessier |
|---|---|
| Primary category | cs.LG |
| Published | 18 August 2026 |
| Last updated at source | 18 August 2026 |
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