2025
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models
NAACL 2025findings
Fine-tuning Large Language Models (LLMs) on specific datasets is a common practice to improve performance on target tasks. However, this performance gain often leads to overfitting, where the model becomes too specialized in either the task or the characteristics of the training data, resulting in a…