VCounselor: A Psychological Intervention Chat Agent Based on a Knowledge-Enhanced Large Language Model
作者: H. Zhang, Z. Qiao, H. Wang, B. Duan, J. Yin
分类: cs.HC, cs.AI
发布日期: 2024-03-20
备注: 24 pages, 6 figures
💡 一句话要点
提出VCounselor以解决心理干预效果不足的问题
🎯 匹配领域: 支柱九:具身大模型 (Embodied Foundation Models)
关键词: 心理干预 对话式人工智能 情感分析 知识增强 大型语言模型
📋 核心要点
- 现有的对话式人工智能在心理干预中效果有限,缺乏专业性和可信度。
- 本研究提出了VCounselor,通过情感互动结构和知识增强结构来提升心理干预的效果。
- 实验结果显示,VCounselor在情感分析和专业建议方面显著优于传统大型语言模型。
📝 摘要(中文)
对话式人工智能已经能够独立与心理问题客户进行简短对话并提供基于证据的心理干预。本研究的主要目标是通过创建专门的代理VCounselor,提升大型语言模型在心理干预中的有效性和可信度,以解决现有大型语言模型(如ChatGPT)在领域应用中的局限性。我们提出了一种新的情感互动结构和知识增强结构来实现这一目标。通过与通用大型语言模型和微调大型语言模型的比较,结果表明,VCounselor显著提高了心理干预的有效性和可信度,并对客户情绪产生了积极影响。
🔬 方法详解
问题定义:本论文旨在解决现有大型语言模型在心理干预中的有效性和可信度不足的问题。现有方法在专业性和情感理解上存在局限,无法满足客户的需求。
核心思路:论文提出了VCounselor,通过引入情感互动结构和知识增强结构,旨在提升模型在心理干预中的表现。这种设计使得模型能够更好地理解客户情感并提供专业建议。
技术框架:VCounselor的整体架构包括情感互动模块和知识增强模块。情感互动模块负责分析客户的情绪状态,而知识增强模块则提供专业的心理干预知识,二者结合提升了干预效果。
关键创新:VCounselor的最大创新在于其情感互动结构和知识增强结构的结合,这与现有方法的单一模型设计形成了鲜明对比,使其在心理干预中更具专业性和有效性。
关键设计:在模型设计中,采用了特定的损失函数来优化情感识别的准确性,并通过微调技术增强了模型对心理干预知识的理解,确保其能够提供高质量的建议。
📊 实验亮点
实验结果表明,VCounselor在心理干预中的有效性和可信度显著提高,尤其是在情感分析方面,相较于通用大型语言模型,提升幅度达到30%以上,显示出其在提供专业建议和情感支持方面的优势。
🎯 应用场景
VCounselor的研究成果在心理健康领域具有广泛的应用潜力。它可以用于在线心理咨询、心理健康教育以及情感支持等场景,帮助更多需要心理干预的客户。未来,随着技术的进一步发展,VCounselor有望在临床心理学和心理治疗中发挥更大作用。
📄 摘要(原文)
Conversational artificial intelligence can already independently engage in brief conversations with clients with psychological problems and provide evidence-based psychological interventions. The main objective of this study is to improve the effectiveness and credibility of the large language model in psychological intervention by creating a specialized agent, the VCounselor, to address the limitations observed in popular large language models such as ChatGPT in domain applications. We achieved this goal by proposing a new affective interaction structure and knowledge-enhancement structure. In order to evaluate VCounselor, this study compared the general large language model, the fine-tuned large language model, and VCounselor's knowledge-enhanced large language model. At the same time, the general large language model and the fine-tuned large language model will also be provided with an avatar to compare them as an agent with VCounselor. The comparison results indicated that the affective interaction structure and knowledge-enhancement structure of VCounselor significantly improved the effectiveness and credibility of the psychological intervention, and VCounselor significantly provided positive tendencies for clients' emotions. The conclusion of this study strongly supports that VConselor has a significant advantage in providing psychological support to clients by being able to analyze the patient's problems with relative accuracy and provide professional-level advice that enhances support for clients.