paper-with-me

홈 › Papers

Enhancing Psychological Counseling with Large Language Model: A Multifaceted Decision-Support System for Non-Professionals

2023-08-29 · Guanghui Fu, Qing Zhao, Jianqiang Li, Dan Luo, Changwei Song, Wei Zhai, Shuo Liu, Fan Wang, Yan Wang, Lijuan Cheng, Juan Zhang, Bing Xiang Yang

In the contemporary landscape of social media, an alarming number of users express negative emotions, some of which manifest as strong suicidal intentions. This situation underscores a profound need for trained psychological counselors who can enact effective mental interventions. However, the development of these professionals is often an imperative but time-consuming task. Consequently, the mobilization of non-professionals or volunteers in this capacity emerges as a pressing concern. Leveraging the capabilities of artificial intelligence, and in particular, the recent advances in large language models, offers a viable solution to this challenge. This paper introduces a novel model constructed on the foundation of large language models to fully assist non-professionals in providing psychological interventions on online user discourses. This framework makes it plausible to harness the power of non-professional counselors in a meaningful way. A comprehensive study was conducted involving ten professional psychological counselors of varying expertise, evaluating the system across five critical dimensions. The findings affirm that our system is capable of analyzing patients' issues with relative accuracy and proffering professional-level strategies recommendations, thereby enhancing support for non-professionals. This research serves as a compelling validation of the application of large language models in the field of psychology and lays the groundwork for a new paradigm of community-based mental health support.

📄 PDF Abstract BibTeX arXiv:2308.15192

Code (1)

GuanghuiFU/counselor_support 공식 구현

Tasks

Language ModelingLanguage ModellingLarge Language Model

Similar Papers 제목 키워드 기반

PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counseling

2024-12-18 · Haojie Xie, YiRong Chen, Xiaofen Xing, Jingkai Lin 외

Currently, large language models (LLMs) have made significant progress in the field of psychological counseling. However, existing mental health LLMs overlook a critical issue where they do not consider the fact that dif…

One-Shot Learning

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

2024-05-26 · Chenhao Zhang, Renhao Li, Minghuan Tan, Min Yang 외

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 t…

Psychological Counseling Ability of Large Language Models

2025-03-01 · Fangyu Peng, Jingxin Nie

With the development of science and the continuous progress of artificial intelligence technology, Large Language Models (LLMs) have begun to be widely utilized across various fields. However, in the field of psychologic…

AutoCBT: An Autonomous Multi-agent Framework for Cognitive Behavioral Therapy in Psychological Counseling

2025-01-16 · Ancheng Xu, Di Yang, Renhao Li, Jingwei Zhu 외

Traditional in-person psychological counseling remains primarily niche, often chosen by individuals with psychological issues, while online automated counseling offers a potential solution for those hesitant to seek help…

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

2026-07-26 · Kaitong Weng, Lixin Liu, Zihao Liu, Bo Wang 외 arxiv

Using large language models (LLMs) to assist psychological counseling is an important task in the field of natural language processing. The construction of high-quality psychological support dialogue corpora serves as a …

Dialogue Generation