PsyDT：使用LLMs构建具有个性化咨询风格的心理咨询师数字孪生以进行心理咨询
PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counseling
AI总结：
针对现有心理健康LLMs忽视咨询师个性化风格的问题，提出PsyDT框架，利用GPT-4通过动态单样本学习捕捉咨询师风格并合成多轮对话数据集，微调LLMs构建具有特定风格的心理咨询师数字孪生，实验证明其优于基线方法。
摘要：
目前，大语言模型（LLMs）在心理咨询领域取得了显著进展。然而，现有的心理健康LLMs忽视了一个关键问题，即它们没有考虑到不同的心理咨询师展现出不同的个人风格，包括语言风格和治疗技术等。因此，这些LLMs无法满足寻求不同咨询风格的来访者的个人需求。为了帮助弥合这一差距，我们提出了PsyDT，一种使用LLMs构建具有个性化咨询风格的心理咨询师数字孪生的新框架。与收集大量真实世界咨询案例以创建特定咨询师数字孪生这种耗时且昂贵的方法相比，我们的框架提供了更快且更具成本效益的解决方案。为了构建PsyDT，我们利用动态单样本学习，通过GPT-4捕捉咨询师独特的咨询风格，主要关注语言风格和治疗技术。随后，利用现有的包含来访者问题的单轮长文本对话，引导GPT-4合成特定咨询师的多轮对话。最后，我们在合成数据集PsyDTCorpus上微调LLMs，以实现具有个性化咨询风格的心理咨询师数字孪生。实验结果表明，我们提出的PsyDT框架能够合成与真实世界咨询案例高度相似的多轮对话，并与其他基线相比展现出更好的性能，从而证明我们的框架能够有效构建具有特定咨询风格的心理咨询师数字孪生。
英文摘要：
Currently, large language models (LLMs) have made significant progress in the field of psychological counseling. However, existing mental health LLMs overlook a critical issue where they do not consider the fact that different psychological counselors exhibit different personal styles, including linguistic style and therapy techniques, etc. As a result, these LLMs fail to satisfy the individual needs of clients who seek different counseling styles. To help bridge this gap, we propose PsyDT, a novel framework using LLMs to construct the Digital Twin of Psychological counselor with personalized counseling style. Compared to the time-consuming and costly approach of collecting a large number of real-world counseling cases to create a specific counselor's digital twin, our framework offers a faster and more cost-effective solution. To construct PsyDT, we utilize dynamic one-shot learning by using GPT-4 to capture counselor's unique counseling style, mainly focusing on linguistic style and therapy techniques. Subsequently, using existing single-turn long-text dialogues with client's questions, GPT-4 is guided to synthesize multi-turn dialogues of specific counselor. Finally, we fine-tune the LLMs on the synthetic dataset, PsyDTCorpus, to achieve the digital twin of psychological counselor with personalized counseling style. Experimental results indicate that our proposed PsyDT framework can synthesize multi-turn dialogues that closely resemble real-world counseling cases and demonstrate better performance compared to other baselines, thereby show that our framework can effectively construct the digital twin of psychological counselor with a specific counseling style.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
