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English(EN) Asclepius: An Adaptive Harness for Long-Horizon Clinical Agents

新的Asclepius代理框架提高了长时程临床LLM的性能

研究人员开发了Asclepius,这是一种新颖的自适应代理框架,旨在提高LLM代理在长时程临床场景中的性能。与通常在短期任务上进行评估的代理不同,Asclepius在模拟的急诊科轮班中进行了测试,揭示了在交付完整和及时的关键操作方面的执行差距。该系统解决了三种故障模式:指令遵循漂移、治疗不完整以及及时性方面的严重程度-公平性差距。Asclepius包含一个自演进框架、一个外部化临床技能库和分区子代理,在保留数据上使关键操作正确性提高了22%,及时性提高了13%。 AI

影响 这项研究可能导致在医疗保健等复杂现实世界环境中出现更强大、更可靠的AI代理,从而提高关键任务的执行效率和及时性。

排序理由 该集群描述了一篇关于LLM新型代理框架的详细研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的Asclepius代理框架提高了长时程临床LLM的性能

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该集群描述了一篇关于LLM新型代理框架的详细研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Grace Chang Yuan, Xiaoman Zhang, Sung Eun Kim, Luyang Luo, Pranav Rajpurkar ·

    Asclepius:面向长时域临床代理的自适应框架

    arXiv:2609.13543v1 Announce Type: new Abstract: LLM agents are predominantly benchmarked on short, single-task trajectories, yet real deployments run for hours under contention, surfacing a different class of failures. We use the Clinical Environment Simulator (CES), in which an …