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Psychological Counseling Cannot Be Achieved Overnight: Automated Psychological Counseling Through Multi-Session Conversations

Published: June 7, 2025 | arXiv ID: 2506.06626v1

By: Junzhe Wang , Bichen Wang , Xing Fu and more

Potential Business Impact:

Helps AI give better, ongoing mental health help.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

In recent years, Large Language Models (LLMs) have made significant progress in automated psychological counseling. However, current research focuses on single-session counseling, which doesn't represent real-world scenarios. In practice, psychological counseling is a process, not a one-time event, requiring sustained, multi-session engagement to progressively address clients' issues. To overcome this limitation, we introduce a dataset for Multi-Session Psychological Counseling Conversation Dataset (MusPsy-Dataset). Our MusPsy-Dataset is constructed using real client profiles from publicly available psychological case reports. It captures the dynamic arc of counseling, encompassing multiple progressive counseling conversations from the same client across different sessions. Leveraging our dataset, we also developed our MusPsy-Model, which aims to track client progress and adapt its counseling direction over time. Experiments show that our model performs better than baseline models across multiple sessions.

Country of Origin
🇨🇳 China

Page Count
15 pages

Category
Computer Science:
Computation and Language