arXiv AI October 9, 2026 By Heng Li, Yong Zhang, Ning Cheng, Zhigen Li, Yun Zhu, Yanmeng Wang, Shaojun Wang, Jing Xiao

PIVOT: Perplexity-Informed KD-to-RL Transition Scheduling for Vertical-Domain Few-Shot Distillation

PIVOT introduces a dynamic transition framework for vertical-domain few-shot distillation, routing samples between On-Policy Distillation (OPD) and GRPO-based reinforcement learning based on teacher-evaluated perplexity. Low-perplexity samples are moved to GRPO for reward-driven refinement, while high-perplexity samples remain under OPD to continue acquiring domain knowledge. Experiments on Banking77 and HWU64 demonstrate that PIVOT outperforms both continued OPD and globally synchronized OPD→GRPO baselines, achieving stronger downstream performance and more stable training dynamics.

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