XrayClaw deploys cooperative-competitive multi-agent alignment and Competitive Preference Optimization to raise diagnostic accuracy, reasoning fidelity, and generalization on chest X-ray benchmarks.
Mllm-as-a-judge: Assessing multimodal llm-as-a-judge with vision- language benchmark
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RadAgents is a multi-agent framework coupling clinical priors with task-aware multimodal reasoning and radiologist-like workflows, plus grounding and retrieval-augmentation for conflict resolution in chest X-ray interpretation.