MARC v1: An Open-Source Multi-Agent Framework for Clinical AI Reasoning and Coordination
MARC breaks clinical reasoning into traceable, role-specific agent stages instead of one large prompt.
The arXiv paper presents an open-source framework for extraction, reasoning, answer generation, and evaluation in clinical AI workflows. Its intermediate outputs are passed explicitly between stages, so failures can be traced to a specific step. A Decomposer module can generate task-specific agent prompts from plain-language descriptions. The system is model-agnostic, YAML-configurable, and supports both API-based and local CPU-compatible deployment. ArXiv · AI/CL/LG's note
The arXiv paper presents an open-source framework for extraction, reasoning, answer generation, and evaluation in clinical AI workflows. Its intermediate outputs are passed explicitly between stages, so failures can be traced to a specific step. A Decomposer module can generate task-specific agent prompts from plain-language descriptions. The system is model-agnostic, YAML-configurable, and supports both API-based and local CPU-compatible deployment. ArXiv · AI/CL/LG's note
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