EmoTrace: An Emotion Trajectory-Centered Framework for Psychological Support Dialogue Generation

2026-07-26 · Source: Computation and Language · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Mental Health & Psychological Support · Depth: Expert, quick

Summary

EmoTrace is a novel framework designed for generating high-quality psychological support dialogue corpora, addressing limitations in current large language models (LLMs) used for counseling. Existing LLMs often fail to effectively respond to emotionally unstable scenarios due to emotionally stable seeker profiles, limited emotional dynamics, and counselors' problem-solving focus over emotion-focused interaction in current datasets. EmoTrace tackles these issues by centering on modeling seekers' emotional trajectories within multi-turn dialogues. It constructs seekers' cognitive profiles and integrates a seeker module with emotional schemas and an activation mechanism, a counselor module, and an emotional trajectory control module. This architecture enhances the complexity of seeker emotional expression and enables more targeted empathic responses from counselors. Experimental results indicate that EmoTrace surpasses existing methods in both emotional richness and empathy quality.

Key takeaway

For NLP Engineers developing conversational AI for psychological support, you should prioritize models capable of handling dynamic emotional states. Current LLMs often overlook emotionally unstable scenarios, limiting their effectiveness. Consider integrating emotional trajectory modeling, like EmoTrace's approach, to generate more empathetic and emotionally rich dialogues. This shift from purely problem-solving responses to emotion-focused interaction will significantly improve the quality and applicability of your counseling-oriented conversational agents.

Key insights

EmoTrace models seeker emotional trajectories to generate psychological support dialogues with enhanced emotional richness and empathy.

Principles

• Psychological support benefits from modeling dynamic emotional states.
• Emotion-focused interaction is crucial in counseling dialogues.
• Cognitive profiles can inform seeker emotional schemas.

Method

EmoTrace generates multi-turn dialogue corpora by constructing seeker cognitive profiles and integrating seeker, counselor, and emotional trajectory control modules to enhance emotional and empathic expression.

In practice

• Develop dialogue systems sensitive to emotional instability.
• Incorporate emotional schemas for dynamic user modeling.
• Prioritize emotion-focused responses in counseling AI.

Topics

• Psychological Support AI
• Dialogue Generation
• Emotional Trajectory Modeling
• Large Language Models
• Empathy in AI
• Conversational AI

Best for: Research Scientist, AI Scientist, NLP Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Computation and Language.