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Asclepius is an adaptive agent scaffolding for long-horizon clinical tasks that improves critical-action correctness by 22% over a baseline agent framework in simulated emergency-department shifts.
This paper introduces Deep Reasoning, an inference-time approach that uses structured meta-reasoning to construct task-specific scaffolds for general-purpose agents. The proposed agent, Dolores, outperforms existing methods by distributing cognition across lower-load reasoning threads, reducing hallucinations and improving performance across multiple benchmarks.