AI PsyRoom: Artificial Intelligence Platform for Segmented Yearning and Reactive Outcome Optimization Method
Journal:
arXiv
Published Date:
Jun 7, 2025
Abstract
Psychological counseling faces huge challenges due to the growing demand for
mental health services and the shortage of trained professionals. Large
language models (LLMs) have shown potential to assist psychological counseling,
especially in empathy and emotional support. However, existing models lack a
deep understanding of emotions and are unable to generate personalized
treatment plans based on fine-grained emotions. To address these shortcomings,
we present AI PsyRoom, a multi-agent simulation framework designed to enhance
psychological counseling by generating empathetic and emotionally nuanced
conversations. By leveraging fine-grained emotion classification and a
multi-agent framework, we construct a multi-agent PsyRoom A for dialogue
reconstruction, generating a high-quality dialogue dataset EmoPsy, which
contains 35 sub-emotions, 423 specific emotion scenarios, and 12,350 dialogues.
We also propose PsyRoom B for generating personalized treatment plans.
Quantitative evaluations demonstrate that AI PsyRoom significantly outperforms
state-of-the-art methods, achieving 18% improvement in problem orientation, 23%
in expression, 24% in Empathy, and 16% in interactive communication quality.
The datasets and models are publicly available, providing a foundation for
advancing AI-assisted psychological counseling research.
