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The paper presents MedPAO-Assist, an edge-deployable, modality-aware agentic AI framework that structures radiology reports from dictation using a ~0.6B-parameter small language model, running with ~3.3GB RAM and ~31s latency on a CPU-only laptop.
The paper presents a locally deployed multi-agent AI system for structuring radiology reports and performing quality assurance, with radiologist evaluation showing favorable performance.
This paper presents AuditFlow, a graph-grounded multi-agent framework that uses executable symbolic environments for structured financial reporting verification, achieving 82.09% audit accuracy on a FinAuditing-derived sample under GPT-5.5.