Dialogue is Better Than Monologue: Instructing Medical LLMs via Strategical Conversations

Understand

Current medical AI systems often fail to replicate real-world clinical reasoning, as they are predominantly trained and evaluated on static text and question-answer tasks.

• These tuning methods and benchmarks overlook critical aspects like evidence-based reasoning and handling distracting information.
• To bridge this gap, we introduce a novel benchmark that simulates real-world diagnostic scenarios, integrating noise and difficulty levels aligned with USMLE standards.
• Moreover, we explore dialogue-based fine-tuning, which transforms static datasets into conversational formats to better capture iterative reasoning processes.