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English(EN) DeepSAGE: Stage-Aware Reinforcement Learning for Structured CBT Counseling Dialogue

AI框架DeepSAGE增强结构化认知行为疗法咨询对话

研究人员开发了DeepSAGE,一个结合大型语言模型(LLMs)和深度强化学习(DRL)的新型框架,用于创建更结构化、目标导向的AI咨询代理。该系统旨在在一场咨询中遵循认知行为疗法(CBT)的十一个阶段,由外部控制器管理阶段完成,DRL模型指导生成响应的治疗意图。使用模拟客户进行的评估表明,与其它方法相比,DeepSAGE提高了对话控制、效率和用户参与度,但仍需要进一步的人类评估来确认其临床有效性和安全性。 AI

影响 这项研究通过改进对话结构和治疗目标实现,有望带来更有效的AI驱动的心理健康支持工具。

排序理由 该集群包含一篇详细介绍特定应用新AI框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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AI框架DeepSAGE增强结构化认知行为疗法咨询对话

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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Qi Zhang, Heajun An, Prakriti Dumaru, Sang Won Lee, Lifu Huang, Pamela J. Wisniewski, Jin-Hee Cho ·

    DeepSAGE:面向结构化CBT咨询对话的阶段感知强化学习

    arXiv:2608.22615v1 Announce Type: new Abstract: Large Language Model (LLM)-based counseling agents can generate fluent and supportive responses, but they often lack the structured, goal-directed progression required to conduct a coherent therapeutic session. We present DeepSAGE (…