Cura 1T: Specialized Model for Agentic Healthcare

Cura 1T：面向智能体医疗的专用模型

Abstract: Healthcare spans high-stakes communication, expert reasoning, and workflow execution, yet specialized LLMs that cover these use cases together remain limited. A healthcare model must handle patient consultation, clinical reasoning over text and images, interactive diagnosis, and electronic health record (EHR) tool use. These capabilities fail in different ways, and a narrow update for one task can degrade another.

摘要： 医疗保健领域涵盖了高风险沟通、专家推理和工作流程执行，然而，能够同时覆盖这些用例的专用大语言模型（LLM）仍然有限。一个医疗模型必须能够处理患者咨询、基于文本和图像的临床推理、交互式诊断以及电子健康记录（EHR）工具的使用。这些能力在不同场景下表现各异，且针对单一任务的微小更新可能会导致其他能力的退化。

We present Cura 1T, a healthcare-specialized LLM trained through a human-gated self-evolution loop. In each evolution round, a training agent plans a target capability, trains the model, evaluates benchmark trajectories, and refines the data mixture from observed failures. This data-centered loop improves the model through targeted synthetic and curated examples rather than a single generic medical-data update.

我们推出了 Cura 1T，这是一个通过“人工门控自进化循环”（human-gated self-evolution loop）训练的医疗专用大语言模型。在每一轮进化中，训练智能体会规划目标能力、训练模型、评估基准轨迹，并根据观察到的失败案例优化数据组合。这种以数据为中心的循环通过有针对性的合成示例和精选数据来改进模型，而不是简单地进行通用的医学数据更新。

Across the healthcare evaluation suite, Cura 1T ranks at or near the top among frontier baselines, while remaining competitive on out-of-domain reasoning and agentic benchmarks.

在医疗评估套件中，Cura 1T 在前沿基准模型中名列前茅，同时在领域外推理和智能体基准测试中也保持了极强的竞争力。

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Paper Details:

• Authors: actAVA AI: Haolin Chen, Leon Qi, Steve Brown, Deon Metelski, Tao Xia, Joonyul Lee, Qixuan Wang, Kevin Riley, Frank Wang, Weiran Yao
• Submission Date: 15 Jul 2026
• arXiv ID: 2607.15314

论文详情：

• 作者： actAVA AI: Haolin Chen, Leon Qi, Steve Brown, Deon Metelski, Tao Xia, Joonyul Lee, Qixuan Wang, Kevin Riley, Frank Wang, Weiran Yao
• 提交日期： 2026年7月15日
• arXiv ID: 2607.15314