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CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling
Zhang, Chenhao1,3; Li, Renhao2,3; Tan, Minghuan3; Yang, Min3; Zhu, Jingwei4; Yang, Di4; Zhao, Jiahao3,5; Ye, Guancheng6; Li, Chengming7; Hu, Xiping7
2024
Conference NameFindings of the 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024
Source PublicationProceedings of the Annual Meeting of the Association for Computational Linguistics
VolumeFindings of the Association for Computational Linguistics: ACL 2024
Pages13947-13966
Conference Date11-16 August 2024
Conference PlaceHybrid, Bangkok
CountryThailand
PublisherAssociation for Computational Linguistics (ACL)
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.

DOI10.18653/v1/2024.findings-acl.830
URLView the original
Language英語English
Scopus ID2-s2.0-85205284352
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionFaculty of Science and Technology
Corresponding AuthorTan, Minghuan; Yang, Min
Affiliation1.Huazhong University of Science and Technology, China
2.University of Macau, Macao
3.Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China
4.University of Science and Technology of China, China
5.Jilin University, China
6.South China University of Technology, China
7.Shenzhen MSU-BIT University, China
Recommended Citation
GB/T 7714
Zhang, Chenhao,Li, Renhao,Tan, Minghuan,et al. CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling[C]:Association for Computational Linguistics (ACL), 2024, 13947-13966.
APA Zhang, Chenhao., Li, Renhao., Tan, Minghuan., Yang, Min., Zhu, Jingwei., Yang, Di., Zhao, Jiahao., Ye, Guancheng., Li, Chengming., & Hu, Xiping (2024). CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Findings of the Association for Computational Linguistics: ACL 2024, 13947-13966.
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