2025
Take the essence and discard the dross: A Rethinking on Data Selection for Fine-Tuning Large Language Models
NAACL 2025long
Data selection for fine-tuning large language models (LLMs) aims to choose a high-quality subset from existing datasets, allowing the trained model to outperform baselines trained on the full dataset. However, the expanding body of research lacks a clear, unified framework, and the variability in ex…