CHECK combines database fact-checking with an ensemble-consistency classifier to flag medical LLM hallucinations, with reported AUCs of 0.95-0.96, but the headline '31% to 0.3%' reduction is a comparison of question context, not of the detection system.
Detec ting hallucinations in large language models using semantic entropy
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Trustworthy AI for Medicine: Continuous Hallucination Detection and Elimination with CHECK
CHECK combines database fact-checking with an ensemble-consistency classifier to flag medical LLM hallucinations, with reported AUCs of 0.95-0.96, but the headline '31% to 0.3%' reduction is a comparison of question context, not of the detection system.