CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling

Chenhao Zhang, Renhao Li, Minghuan Tan*, Min Yang*, Jingwei Zhu, Di Yang, Jiahao Zhao, Guancheng Ye, Chengming Li, Xiping Hu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Using large language models (LLMs) to assist psychological counseling is a significant but challenging task at present. Attempts have been made on improving empathetic conversations or acting as effective assistants in the treatment with LLMs. However, the existing datasets lack consulting knowledge, resulting in LLMs lacking professional consulting competence. Moreover, how to automatically evaluate multi-turn dialogues within the counseling process remains an understudied area. To bridge the gap, we propose CPsyCoun, a report-based multi-turn dialogue reconstruction and evaluation framework for Chinese psychological counseling. To fully exploit psychological counseling reports, a two-phase approach is devised to construct high-quality dialogues while a comprehensive evaluation benchmark is developed for the effective automatic evaluation of multi-turn psychological consultations. Competitive experimental results demonstrate the effectiveness of our proposed framework in psychological counseling. We open-source the datasets and model for future research..

Original languageEnglish
Title of host publicationThe 62nd Annual Meeting of the Association for Computational Linguistics
Subtitle of host publicationFindings of the Association for Computational Linguistics, ACL 2024
EditorsLun-Wei Ku, Andre Martins, Vivek Srikumar
PublisherAssociation for Computational Linguistics (ACL)
Pages13947-13966
Number of pages20
ISBN (Electronic)9798891760998
DOIs
Publication statusPublished - 2024
Externally publishedYes
EventFindings of the 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024 - Hybrid, Bangkok, Thailand
Duration: 11 Aug 202416 Aug 2024

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

ConferenceFindings of the 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024
Country/TerritoryThailand
CityHybrid, Bangkok
Period11/08/2416/08/24

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