Preprint
Jul 2026
Stable Miscalibration in Large Language Models: A Practical View of High-Confidence Errors
This work combines two diagnostics: a label-aware output-level audit score that ranks domains by confidence variation and overconfident mistakes under a forced-answer baseline, and an internal sensitivity probe that measures hidden-state movement.
A. Okutomi
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