Preprint
Sep 2026
Data-Free On-Policy Distillation: How Far Can We Go Without External Data?
On-policy distillation (OPD) is increasingly applied to frontier foundation model post-training. Prior work in this area has largely focused on algorithmic advances, yet it remains unclear how much OPD depends on its training questions and, in particular, how far this dependence can be reduced. Across two representativ...
Gengsheng Li, Mao Zheng, Ming-Yang Song et al.
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