A dual clinical-computational taxonomy for medical LLM reasoning plus a five-level 5k-sample benchmark showing specialists excel at diagnosis and general models at decision support/dialogue.
arXiv preprint arXiv:2506.13793 (2025)
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Chain-of-thought underperforms direct answering in medical VQA due to a perception bottleneck, but ROI cues and textual grounding interventions can improve results and reverse the gap.
MRPO is a step-aware RL method that penalizes early reasoning errors exponentially more when the final answer is incorrect, reducing early-stage failures from 64% to 13% and outperforming baselines including larger models on medical VQA tasks.
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Aligning Clinical Needs and AI Capabilities: A Survey on LLMs for Medical Reasoning
A dual clinical-computational taxonomy for medical LLM reasoning plus a five-level 5k-sample benchmark showing specialists excel at diagnosis and general models at decision support/dialogue.
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Better Eyes, Better Thoughts: Why Vision Chain-of-Thought Fails in Medicine
Chain-of-thought underperforms direct answering in medical VQA due to a perception bottleneck, but ROI cues and textual grounding interventions can improve results and reverse the gap.
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Breaking Failure Cascades: Step-Aware Reinforcement Learning for Medical Multimodal Reasoning
MRPO is a step-aware RL method that penalizes early reasoning errors exponentially more when the final answer is incorrect, reducing early-stage failures from 64% to 13% and outperforming baselines including larger models on medical VQA tasks.