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iSDFT: Information-Proximal Self-Distillation for Continual Learning in LLMs

Khamis, Ahmed Khaled et al.
arXiv (All) · Papers
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machine-learning
On-policy self-distillation fine-tuning (SDFT) learns new skills from demonstrations while reducing forgetting, but it always distils toward the full demonstration-conditioned teacher. This fixes teacher influence at the full-teacher endpoint, providing no control over how much demonstration informa
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