reasoning-mismatch

CLExEval introduces a human-in-the-loop framework for evaluating LLM clinical reasoning under progressive information masking, revealing failure patterns such as verbosity bias, hidden knowledge paradox, and reasoning-to-output mismatch in models like GPT-4o-mini and HuatuoGPT-o1.