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Large Language ModelsarXiv cs.AIPublished: Apr 2, 2026, 13:00 JST

Researchers propose Truth AnChoring method to fix unreliable uncertainty detection in large language models by calibrating metrics against actual factual correctness.

Researchers propose Truth AnChoring method to fix unreliable uncertainty detection in large language models by calibrating metrics against actual factual correctness.

Uncertainty estimation (UE) metrics in LLMs often fail to reliably detect hallucinations due to 'proxy failure'—they measure model behavior rather than actual factual accuracy

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