Go to ACL ARR 2025 May homepageMIND: Towards Immersive Psychological Healing with Multi-Agent Inner Dialogue
Abstract: Mental health issues are worsening in today's competitive society, such as depression and anxiety.
Traditional healings like counseling and chatbots fail to engage effectively, they often provide generic responses lacking emotional depth. Although large language models (LLMs) have the potential to create more human-like interactions, they still struggle to capture subtle emotions. This requires LLMs to be equipped with human-like adaptability and warmth.
To fill this gap, we propose the $MIND$ ($M$ulti-agent $IN$ner $D$ialogue), a novel paradigm that provides more immersive psychological healing environments.
Considering the strong generative and role-playing ability of LLM agents, we predefine an interactive healing framework and assign LLM agents different roles within the framework to engage in interactive inner dialogues with users, thereby providing an immersive healing experience.
We conduct extensive human experiments in various real-world healing dimensions, and find that $MIND$ provides a more user-friendly experience than traditional paradigms. This demonstrates that $MIND$ effectively leverages the significant potential of LLMs in psychological healing.
Paper Type: Long
Research Area: Language Modeling
Research Area Keywords: LLM/AI agents
Languages Studied: English
Submission Number: 6782
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