VCounselor: A Psychological Intervention Chat Agent Based on a Knowledge-Enhanced Large Language Model

• URL: http://arxiv.org/abs/2403.13553v1
• Date: Wed, 20 Mar 2024 12:46:02 GMT
• Title: VCounselor: A Psychological Intervention Chat Agent Based on a Knowledge-Enhanced Large Language Model
• Authors: H. Zhang, Z. Qiao, H. Wang, B. Duan, J. Yin,
• Abstract summary: The main objective of this study is to improve the effectiveness and credibility of the large language model in psychological intervention. We achieved this goal by proposing a new affective interaction structure and knowledge-enhancement structure. The comparison results indicated that the affective interaction structure and knowledge-enhancement structure of VCounselor significantly improved the effectiveness and credibility of the psychological intervention.
• Score: 1.0055768887247036
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Conversational artificial intelligence can already independently engage in brief conversations with clients with psychological problems and provide evidence-based psychological interventions. The main objective of this study is to improve the effectiveness and credibility of the large language model in psychological intervention by creating a specialized agent, the VCounselor, to address the limitations observed in popular large language models such as ChatGPT in domain applications. We achieved this goal by proposing a new affective interaction structure and knowledge-enhancement structure. In order to evaluate VCounselor, this study compared the general large language model, the fine-tuned large language model, and VCounselor's knowledge-enhanced large language model. At the same time, the general large language model and the fine-tuned large language model will also be provided with an avatar to compare them as an agent with VCounselor. The comparison results indicated that the affective interaction structure and knowledge-enhancement structure of VCounselor significantly improved the effectiveness and credibility of the psychological intervention, and VCounselor significantly provided positive tendencies for clients' emotions. The conclusion of this study strongly supports that VConselor has a significant advantage in providing psychological support to clients by being able to analyze the patient's problems with relative accuracy and provide professional-level advice that enhances support for clients.

Related papers

• Interactive Dialogue Agents via Reinforcement Learning on Hindsight Regenerations [58.65755268815283]
  Many real dialogues are interactive, meaning an agent's utterances will influence their conversational partner, elicit information, or change their opinion. We use this fact to rewrite and augment existing suboptimal data, and train via offline reinforcement learning (RL) an agent that outperforms both prompting and learning from unaltered human demonstrations. Our results in a user study with real humans show that our approach greatly outperforms existing state-of-the-art dialogue agents.
  arXiv  Detail & Related papers  (2024-11-07T21:37:51Z)
• Enhancing AI-Driven Psychological Consultation: Layered Prompts with Large Language Models [44.99833362998488]
  We explore the use of large language models (LLMs) like GPT-4 to augment psychological consultation services. Our approach introduces a novel layered prompting system that dynamically adapts to user input. We also develop empathy-driven and scenario-based prompts to enhance the LLM's emotional intelligence.
  arXiv  Detail & Related papers  (2024-08-29T05:47:14Z)
• PersLLM: A Personified Training Approach for Large Language Models [66.16513246245401]
  We propose PersLLM, integrating psychology-grounded principles of personality: social practice, consistency, and dynamic development. We incorporate personality traits directly into the model parameters, enhancing the model's resistance to induction, promoting consistency, and supporting the dynamic evolution of personality.
  arXiv  Detail & Related papers  (2024-07-17T08:13:22Z)
• Cactus: Towards Psychological Counseling Conversations using Cognitive Behavioral Theory [24.937025825501998]
  We create a multi-turn dialogue dataset that emulates real-life interactions using the goal-oriented and structured approach of Cognitive Behavioral Therapy (CBT) We benchmark against established psychological criteria used to evaluate real counseling sessions, ensuring alignment with expert evaluations. Experimental results demonstrate that Camel, a model trained with Cactus, outperforms other models in counseling skills, highlighting its effectiveness and potential as a counseling agent.
  arXiv  Detail & Related papers  (2024-07-03T13:41:31Z)
• CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling [27.193022503592342]
  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. A comprehensive evaluation benchmark is developed for the effective automatic evaluation of multi-turn psychological consultations.
  arXiv  Detail & Related papers  (2024-05-26T05:18:00Z)
• COCOA: CBT-based Conversational Counseling Agent using Memory Specialized in Cognitive Distortions and Dynamic Prompt [13.763448771196456]
  We develop a psychological counseling agent that applies Cognitive Behavioral Therapy (CBT) techniques to identify and address cognitive distortions inherent in the client's statements. We construct a memory system to efficiently manage information necessary for counseling while extracting high-level insights about the client.
  arXiv  Detail & Related papers  (2024-02-27T14:38:47Z)
• K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning [83.19215082550163]
  We propose K-ESConv, a novel prompt learning based knowledge injection method for emotional support dialogue system. We evaluate our model on an emotional support dataset ESConv, where the model retrieves and incorporates knowledge from external professional emotional Q&A forum.
  arXiv  Detail & Related papers  (2023-12-16T08:10:10Z)
• ChatCounselor: A Large Language Models for Mental Health Support [8.639639227401625]
  ChatCounselor is a large language model (LLM) solution designed to provide mental health support. The training dataset, Psych8k, was constructed from 260 in-depth interviews, each spanning an hour. ChatCounselor surpasses existing open-source models in the counseling Bench and approaches the performance level of ChatGPT.
  arXiv  Detail & Related papers  (2023-09-27T07:57:21Z)
• Enhancing Psychological Counseling with Large Language Model: A Multifaceted Decision-Support System for Non-Professionals [31.01304974679576]
  This paper introduces a novel model constructed on the foundation of large language models to assist non-professionals in providing psychological interventions on online user discourses. A comprehensive study was conducted involving ten professional psychological counselors of varying expertise, evaluating the system. The findings affirm that our system is capable of analyzing patients' issues with relative accuracy and proffering professional-level strategies recommendations.
  arXiv  Detail & Related papers  (2023-08-29T10:20:53Z)
• Can You be More Social? Injecting Politeness and Positivity into Task-Oriented Conversational Agents [60.27066549589362]
  Social language used by human agents is associated with greater users' responsiveness and task completion. The model uses a sequence-to-sequence deep learning architecture, extended with a social language understanding element. Evaluation in terms of content preservation and social language level using both human judgment and automatic linguistic measures shows that the model can generate responses that enable agents to address users' issues in a more socially appropriate way.
  arXiv  Detail & Related papers  (2020-12-29T08:22:48Z)
• You Impress Me: Dialogue Generation via Mutual Persona Perception [62.89449096369027]
  The research in cognitive science suggests that understanding is an essential signal for a high-quality chit-chat conversation. Motivated by this, we propose P2 Bot, a transmitter-receiver based framework with the aim of explicitly modeling understanding.
  arXiv  Detail & Related papers  (2020-04-11T12:51:07Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.