Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning

Jinlong Pang, Na Di, Zhaowei Zhu +4

Recent studies show that in supervised fine-tuning (SFT) of large language models (LLMs), data quality matters more than quantity. While most data cleaning methods concentrate on f…