用多智能体自动做心理认知行为治疗，更精准更有效。
AutoCBT: An Autonomous Multi-agent Framework for Cognitive Behavioral Therapy in Psychological Counseling
- 构建动态路由的多智能体框架，模拟真实咨询流程
- 在双语数据集上表现优于固定结构模型
- 适合需要匿名支持的心理求助者
传统面对面心理咨询仍属小众，而在线自动化咨询可为因羞耻感不愿求助者提供替代方案。认知行为疗法（CBT）是心理辅导中常用且关键的方法。大语言模型（LLMs）与智能体技术的发展使自动进行CBT诊断与治疗成为可能。然而，现有基于LLM的CBT系统多采用固定结构智能体，限制了自我优化能力，或因重复响应模式导致建议空洞无用。本文利用Quora-like和YiXinLi单轮咨询模型构建通用智能体框架，生成高质量单轮心理咨询服务。通过双语数据集评估各框架生成的单次回复质量。进一步引入受真实心理咨询启发的动态路由与监督机制，构建面向CBT的自主多智能体框架，验证其通用性。实验表明，AutoCBT能提供更高质量的自动化心理咨询服务。
原文摘要 · Abstract (English)
Traditional in-person psychological counseling remains primarily niche, often chosen by individuals with psychological issues, while online automated counseling offers a potential solution for those hesitant to seek help due to feelings of shame. Cognitive Behavioral Therapy (CBT) is an essential and widely used approach in psychological counseling. The advent of large language models (LLMs) and agent technology enables automatic CBT diagnosis and treatment. However, current LLM-based CBT systems use agents with a fixed structure, limiting their self-optimization capabilities, or providing hollow, unhelpful suggestions due to redundant response patterns. In this work, we utilize Quora-like and YiXinLi single-round consultation models to build a general agent framework that generates high-quality responses for single-turn psychological consultation scenarios. We use a bilingual dataset to evaluate the quality of single-response consultations generated by each framework. Then, we incorporate dynamic routing and supervisory mechanisms inspired by real psychological counseling to construct a CBT-oriented autonomous multi-agent framework, demonstrating its general applicability. Experimental results indicate that AutoCBT can provide higher-quality automated psychological counseling services.
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