Author

Seohyun Lee

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#machine learning Preprint Sep 2026

Fisher-Informed Recalibration for Feedback-Based On-Policy Self-Distillation of LLMs

Fire (Fisher-Informed REcalibration), a dual-branch framework that recalibrates the supervision applied to correct and incorrect on-policy outputs during fine-tuning, is proposed, which provides substantially more stable self-distillation while maintaining strong downstream performance, particularly in settings where s...

Seohyun Lee, Dong-Jun Han, Seyyedali Hosseinalipour et al. · 0 citations

Preprint Aug 2026

Reason in the Words You Speak: Idiolectal Paraphrasing Off-Policy Traces for Reasoning Distillation in VideoLLMs

Echo-GRPO is proposed, a framework that lets the model reason in the words it speaks, and idiolectal paraphrasing is a plug-in module that consistently improves both RL and supervised fine-tuning frameworks for reasoning distillation, demonstrating that policy-aligned supervision extends beyond GRPO.

Ji Soo Lee, Jinyoung Park, Seohyun Lee et al. · 0 citations