AI Research
Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts
Large language models (LLMs) are increasingly integrated into clinical workflows, stressing the need for reliable traceability of model-generated output with watermarking. Yet, most watermarks are evaluated on general-purpose benchmarks, leaving domains like medicine, where small...
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ArXiv CS.AI
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ArXiv CS.AI
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Watermarking LLMs for medical use risks introducing clinically significant errors, as standard evaluation methods fail to capture domain-specific failures like terminology corruption or hallucinated content. Rigorous, human-verified medical task benchmarks are essential before deploying such models in healthcare.
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