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EMNLP Findings2025

AuraDial: A Large-Scale Human-Centric Dialogue Dataset for Chinese AI Psychological Counseling

Xiantao Zhang

Abstract

This paper introduces AURADIAL, a largescale, human-centric dialogue dataset for Chinese AI psychological counseling, comprising over 300,000 single-turn dialogues and 90,000 multi-turn dialogue sessions. A key distinction of AURADIAL is its instruction set, primarily derived from real-world user queries, better reflecting genuine expression patterns compared to synthetic or template-based alternatives. Furthermore, we propose an innovative rephrasingbased data generation methodology designed to foster more human-like and empathetic responses, addressing a common shortcoming in AI-generated dialogue. Experimental results demonstrate that models fine-tuned on AURA-DIAL significantly outperform those trained on other public datasets in generating empathetic and relevant replies. AURADIAL offers a novel, valuable resource to the Chinese NLP community for advancing AI in psychological counseling.

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