2025
Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach
ICML 2025poster
One of the key technologies for the success of Large Language Models (LLMs) is preference alignment. However, a notable side effect of preference alignment is poor calibration: while the pre-trained models are typically well-calibrated, LLMs tend to become poorly calibrated after alignment with huma…