Reclaiming Low-Quality Instruction Data with Rule-Guided LLM Reconstruction

Zile Yang, Ling Li, Na Di +5

Data selection for supervised fine-tuning (SFT) often discards low-scoring instruction examples that may retain useful supervision. We propose a rule-guided LLM reconstruction fram…