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New LLM method generates synthetic therapy conversations

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method called SQPsych (Structured Questionnaire-based Psychotherapy) to generate synthetic therapist-client conversations using large language models (LLMs). This approach utilizes structured client profiles and psychological questionnaires without compromising sensitive data. The generated conversations, forming the SQPsychConv corpus, were used to fine-tune open-weight LLMs, resulting in models (SQPsychLLM) that demonstrate improved therapist roleplaying capabilities, as validated by expert psychotherapists. AI

IMPACT This research could accelerate the development of AI-powered mental health tools by providing a method for generating realistic, privacy-preserving synthetic conversation data.

RANK_REASON The cluster describes a research paper detailing a new method and corpus for synthetic data generation in mental health. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New LLM method generates synthetic therapy conversations

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The cluster describes a research paper detailing a new method and corpus for synthetic data generation in mental health. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Doan Nam Long Vu, Rui Tan, Lena Moench, Svenja Jule Francke, Daniel Woiwod, Florian Thomas-Odenthal, Sanna Stroth, Tilo Kircher, Christiane Hermann, Udo Dannlowski, Hamidreza Jamalabadi, Simone Balloccu, Shaoxiong Ji ·

    Roleplaying with Structure: Synthetic Therapist-Client Conversation Generation from Questionnaires

    arXiv:2510.25384v2 Announce Type: replace Abstract: Large Language Models (LLMs) are promising tools for synthetic data generation in mental health. However, privacy policies and restrictions forced previous work to rely mainly on generic information. We present a comprehensive c…

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