Author

Yan Gao

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Preprint Aug 2026

PCSD: Persistent Consistency for Self-Distillation in Agentic Reinforcement Learning

Persistent Consistency Self-Distillation (PCSD) is proposed, which derives token-level distillation weights from the local persistence of teacher-favoring signals, and combines adaptive windows with exponentially decayed aggregation to capture persistent relative teacher support.

Chunji Lv, Yangguang Wei, Junlin Liu et al. · 0 citations