AI RESEARCH
Can Large Language Models Self-Correct in Medical Question Answering? An Exploratory Study
arXiv CS.CL
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ArXi:2604.00261v2 Announce Type: new Large language models (LLMs) have achieved strong performance on medical question answering (medical QA), and chain-of-thought (CoT) prompting has further improved results by eliciting explicit intermediate reasoning; meanwhile, self-reflective (self-corrective) prompting has been widely claimed to enhance model reliability by prompting LLMs to critique and revise their own reasoning, yet its effectiveness in safety-critical medical settings remains unclear.