arXiv cs.CLPaper
Untangling the Mechanisms of Misleading Context in Medical Question Answering
This matters for production medical AI systems. The key finding is that models disclose the misleading context in their reasoning trace 81-98% of the time but only 7-90% of the time in their final response, meaning the problem is often hiding in plain sight. If you're building medical LLM systems, add a verification step that checks whether the model mentioned its sources in the response, not just in the reasoning.