Psychological Counseling Cannot Be Achieved Overnight: Automated Psychological Counseling Through Multi-Session Conversations

• URL: http://arxiv.org/abs/2506.06626v1
• Date: Sat, 07 Jun 2025 02:00:45 GMT
• Title: Psychological Counseling Cannot Be Achieved Overnight: Automated Psychological Counseling Through Multi-Session Conversations
• Authors: Junzhe Wang, Bichen Wang, Xing Fu, Yixin Sun, Yanyan Zhao, Bing Qin,
• Abstract summary: We introduce a dataset for Multi-Session Psychological Counseling Conversation dataset (MusPsy-Dataset)<n>Our MusPsy-Dataset is constructed using real client profiles from publicly available psychological case reports.<n>We also developed our MusPsy-Model, which aims to track client progress and adapt its counseling direction over time.
• Score: 26.422675063457827
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In recent years, Large Language Models (LLMs) have made significant progress in automated psychological counseling. However, current research focuses on single-session counseling, which doesn't represent real-world scenarios. In practice, psychological counseling is a process, not a one-time event, requiring sustained, multi-session engagement to progressively address clients' issues. To overcome this limitation, we introduce a dataset for Multi-Session Psychological Counseling Conversation Dataset (MusPsy-Dataset). Our MusPsy-Dataset is constructed using real client profiles from publicly available psychological case reports. It captures the dynamic arc of counseling, encompassing multiple progressive counseling conversations from the same client across different sessions. Leveraging our dataset, we also developed our MusPsy-Model, which aims to track client progress and adapt its counseling direction over time. Experiments show that our model performs better than baseline models across multiple sessions.

Related papers

• Reframe Your Life Story: Interactive Narrative Therapist and Innovative Moment Assessment with Large Language Models [92.93521294357058]
  Narrative therapy helps individuals transform problematic life stories into empowering alternatives.<n>Current approaches lack realism in specialized psychotherapy and fail to capture therapeutic progression over time.<n>Int (Interactive Narrative Therapist) simulates expert narrative therapists by planning therapeutic stages, guiding reflection levels, and generating contextually appropriate expert-like responses.
  arXiv  Detail & Related papers  (2025-07-27T11:52:09Z)
• KokoroChat: A Japanese Psychological Counseling Dialogue Dataset Collected via Role-Playing by Trained Counselors [1.3456699275044242]
  This study adopts a role-playing approach where trained counselors simulate counselor-client interactions.<n>We construct KokoroChat, a Japanese psychological counseling dialogue dataset comprising 6,589 long-form dialogues.<n> Experimental results demonstrate that fine-tuning open-source LLMs with KokoroChat improves both the quality of generated counseling responses and the automatic evaluation of counseling dialogues.
  arXiv  Detail & Related papers  (2025-06-02T06:20:53Z)
• Psy-Copilot: Visual Chain of Thought for Counseling [11.997628014543773]
  Psy-COT is a graph designed to visualize the thought processes of large language models (LLMs) during therapy sessions.<n>Psy-Copilot is a conversational AI assistant designed to assist human psychological therapists in their consultations.<n>The Psy-Copilot is designed not to replace psychotherapists but to foster collaboration between AI and human therapists.
  arXiv  Detail & Related papers  (2025-03-05T16:23:15Z)
• Consistent Client Simulation for Motivational Interviewing-based Counseling [38.27487999477332]
  We propose a novel framework that supports consistent client simulation for mental health counseling.<n>Our framework tracks the mental state of a simulated client, controls its state transitions, and generates for each state behaviors consistent with the client's motivation, beliefs, preferred plan to change, and receptivity.
  arXiv  Detail & Related papers  (2025-02-05T00:58:30Z)
• AutoCBT: An Autonomous Multi-agent Framework for Cognitive Behavioral Therapy in Psychological Counseling [57.054489290192535]
  Traditional in-person psychological counseling remains primarily niche, often chosen by individuals with psychological issues.<n>Online automated counseling offers a potential solution for those hesitant to seek help due to feelings of shame.
  arXiv  Detail & Related papers  (2025-01-16T09:57:12Z)
• PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counseling [12.08584138023052]
  We propose PsyDT, a novel framework to construct the Digital Twin of Psychological counselor with personalized counseling style.<n>Compared to the time-consuming and costly approach of collecting a large number of real-world counseling cases, our framework offers a faster and more cost-effective solution.
  arXiv  Detail & Related papers  (2024-12-18T09:38:43Z)
• MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders [59.515827458631975]
  Mental health disorders are one of the most serious diseases in the world.<n>Privacy concerns limit the accessibility of personalized treatment data.<n>MentalArena is a self-play framework to train language models.
  arXiv  Detail & Related papers  (2024-10-09T13:06:40Z)
• 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)
• LLM Questionnaire Completion for Automatic Psychiatric Assessment [49.1574468325115]
  We employ a Large Language Model (LLM) to convert unstructured psychological interviews into structured questionnaires spanning various psychiatric and personality domains. The obtained answers are coded as features, which are used to predict standardized psychiatric measures of depression (PHQ-8) and PTSD (PCL-C)
  arXiv  Detail & Related papers  (2024-06-09T09:03:11Z)
• Helping the Helper: Supporting Peer Counselors via AI-Empowered Practice and Feedback [46.70617195649979]
  CARE is an AI-based tool to empower and train peer counselors through practice and feedback.<n> CARE helps diagnose which counseling strategies are needed in a given situation and suggests example responses to counselors during their practice sessions.
  arXiv  Detail & Related papers  (2023-05-15T19:48:59Z)
• Towards Persona-Based Empathetic Conversational Models [58.65492299237112]
  Empathetic conversational models have been shown to improve user satisfaction and task outcomes in numerous domains. In Psychology, persona has been shown to be highly correlated to personality, which in turn influences empathy. We propose a new task towards persona-based empathetic conversations and present the first empirical study on the impact of persona on empathetic responding.
  arXiv  Detail & Related papers  (2020-04-26T08:51:01Z)

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.