Article

Medical Hallucination in Foundation Models and Their Impact on Healthcare

2025-03-03

Abstract excerpt

Hallucinations in foundation models arise from autoregressive training objectives that prioritize token-likelihood optimization over epistemic accuracy, fostering overconfidence and poorly calibrated uncertainty. We define medical hallucination as any model-generated output that is factually incorrect, logically inconsistent, or unsupported by authoritative clinical evidence in ways that could alter clinical decis...

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Literature Corpus work: effcd4dc-3ca0-5ef0-a464-b194f9e99879
DOI: 10.1101/2025.02.28.25323115

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