Calibrating LLMs

Calibrating LLMs involves adjusting models so their confidence scores accurately reflect their actual accuracy. Well-calibrated models express appropriate uncertainty - being confident when correct and uncertain when likely wrong. This helps users better trust and interpret model outputs, especially in critical applications where uncertainty awareness is crucial.