用AI打造可自适应的心理健康助手，实时提供个性化支持。
SouLLMate: An Application Enhancing Diverse Mental Health Support with Adaptive LLMs, Prompt Engineering, and RAG Techniques
- 结合大模型与检索增强生成，实现动态对话与风险识别。
- 在真实自杀倾向数据上验证，风险检测准确率达87.3%。
- 适合心理服务开发者、AI医疗研究者参考应用。
心理健康问题严重影响个人生活，但许多人仍无法获得所需帮助。本研究旨在通过前沿AI技术提供多样、可及、无歧视、个性化且实时的心理健康支持。主要贡献包括：(1) 系统调研近期心理健康支持方法，识别主流功能与未满足需求；(2) 提出SouLLMate，一个基于自适应大模型的系统，融合链式推理、检索增强生成（RAG）、提示工程与领域知识，具备风险检测与主动引导对话等高级功能，并利用RAG支持用户资料上传与对话信息提取；(3) 构建新颖评估方法，基于专业标注访谈数据与真实自杀倾向数据进行初步评估与风险检测测试；(4) 提出关键指标总结（KIS）、主动提问策略（PQS）与堆叠多模型推理（SMMR），通过上下文敏感响应调整、语义连贯性评估与长上下文推理精度提升，增强模型性能与可用性。该研究推动心理健康技术支持发展，有望提升全球心理医疗服务的可及性与有效性。
原文摘要 · Abstract (English)
Mental health issues significantly impact individuals' daily lives, yet many do not receive the help they need even with available online resources. This study aims to provide diverse, accessible, stigma-free, personalized, and real-time mental health support through cutting-edge AI technologies. It makes the following contributions: (1) Conducting an extensive survey of recent mental health support methods to identify prevalent functionalities and unmet needs. (2) Introducing SouLLMate, an adaptive LLM-driven system that integrates LLM technologies, Chain, Retrieval-Augmented Generation (RAG), prompt engineering, and domain knowledge. This system offers advanced features such as Risk Detection and Proactive Guidance Dialogue, and utilizes RAG for personalized profile uploads and Conversational Information Extraction. (3) Developing novel evaluation approaches for preliminary assessments and risk detection via professionally annotated interview data and real-life suicide tendency data. (4) Proposing the Key Indicator Summarization (KIS), Proactive Questioning Strategy (PQS), and Stacked Multi-Model Reasoning (SMMR) methods to enhance model performance and usability through context-sensitive response adjustments, semantic coherence evaluations, and enhanced accuracy of long-context reasoning in language models. This study contributes to advancing mental health support technologies, potentially improving the accessibility and effectiveness of mental health care globally.
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