mlsanityData to 7 Oct 2026

Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Models

arXiv 2307.11991 ↗First posted 22 Jul 2023cs.CL cs.AIcited by 36

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Abstract (arXiv)

The demand for psychological counselling has grown significantly in recent years, particularly with the global outbreak of COVID-19, which has heightened the need for timely and professional mental health support. Online psychological counselling has emerged as the predominant mode of providing services in response to this demand. In this study, we propose the Psy-LLM framework, an AI-based assistive tool leveraging Large Language Models (LLMs) for question-answering in psychological consultation settings to ease the demand for mental health professions. Our framework combines pre-trained LLMs with real-world professional Q&A from psychologists and extensively crawled psychological articles. The Psy-LLM framework serves as a front-end tool for healthcare professionals, allowing them to provide immediate responses and mindfulness activities to alleviate patient stress. Additionally, it functions as a screening tool to identify urgent cases requiring further assistance. We evaluated the framework using intrinsic metrics, such as perplexity, and extrinsic evaluation metrics, with human participant assessments of response helpfulness, fluency, relevance, and logic. The results demonstrate the effectiveness of the Psy-LLM framework in generating coherent and relevant answers to psychological questions. This article discusses the potential and limitations of using large language models to enhance mental health support through AI technologies.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). Builds on 12 of its 63 references that are in the map. First posted on arXiv 22 Jul 2023.

Builds on

12 of 63 references.

References · 12

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  5. 2021PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Supportcited by 92
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 17; 2025: 9; 2026: 3.

36 papers.

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  1. 2023Large language models in healthcare and medical domain: A reviewcited by 126
  2. 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 123
  3. 2024From Matching to Generation: A Survey on Generative Information Retrievalcited by 89
  4. 2024The opportunities and risks of large language models in mental healthcited by 54
  5. 2023ChatCounselor: A Large Language Models for Mental Health Supportcited by 44
  6. 2024Large Language Models in Mental Health Care: a Scoping Reviewcited by 34
  7. 2024PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluationcited by 26
  8. 2024T-RAG: Lessons from the LLM Trenchescited by 23
  9. 2024Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contextscited by 19
  10. 2023User Modeling in the Era of Large Language Models: Current Research and Future Directionscited by 18
  11. 2023Challenges of Large Language Models for Mental Health Counselingcited by 16
  12. 2024Large Language Model for Mental Health: A Systematic Reviewcited by 14
24 more
  1. 2025MindEval: Benchmarking Language Models on Multi-turn Mental Health Supportcited by 9
  2. 2023Towards a Psychological Generalist AI: A Survey of Current Applications of Large Language Models and Future Prospectscited by 8
  3. 2024Digital Diagnostics: The Potential Of Large Language Models In Recognizing Symptoms Of Common Illnessescited by 8
  4. 2025HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agentscited by 6
  5. 2024A New Era in Human Factors Engineering: A Survey of the Applications and Prospects of Large Multimodal Modelscited by 5
  6. 2025Labeling Free-text Data using Language Model Ensemblescited by 5
  7. 2025FedMentor: Domain-Aware Differential Privacy for Heterogeneous Federated LLMs in Mental Healthcited by 5
  8. 2023Interpretable Medical Imagery Diagnosis with Self-Attentive Transformers: A Review of Explainable AI for Health Carecited by 4
  9. 2024Bioinformatics and Biomedical Informatics with ChatGPT: Year One Reviewcited by 4
  10. 2024A Survey of Foundation Models for Music Understandingcited by 4
  11. 2024Analyzing Nobel Prize Literature with Large Language Modelscited by 4
  12. 2024Enhancing Psychotherapy Counseling: A Data Augmentation Pipeline Leveraging Large Language Models for Counseling Conversationscited by 3
  13. 2026Using LLM-as-a-Judge/Jury to Advance Scalable, Clinically-Validated Safety Evaluations of Model Responses to Users Demonstrating Psychosiscited by 3
  14. 2024Optimizing Psychological Counseling with Instruction-Tuned Large Language Modelscited by 2
  15. 2024PsychoLex: Unveiling the Psychological Mind of Large Language Modelscited by 2
  16. 2026PsychAgent: An Experience-Driven Lifelong Learning Agent for Self-Evolving Psychological Counselorcited by 2
  17. 2025P-ReMIS: Pragmatic Reasoning in Mental Health and a Social Implicationcited by 1
  18. 2025Scaling behavior of large language models in emotional safety classification across sizes and taskscited by 1
  19. 2025MoPHES:Leveraging on-device LLMs as Agent for Mobile Psychological Health Evaluation and Supportcited by 1
  20. 2024Enhancing AI-Driven Psychological Consultation: Layered Prompts with Large Language Modelscited by 0
  21. 2024NOVI : Chatbot System for University Novice with BERT and LLMscited by 0
  22. 2025MDD-Thinker: Towards Large Reasoning Models for Major Depressive Disorder Diagnosiscited by 0
  23. 2025Investigating AI in Peer Support via Multi-Module System-Driven Embodied Conversational Agentscited by 0
  24. 2026PsyBridge: A Hybrid Intelligent Framework for Multi-Dimensional Mental Health Assessment and Decision Supportcited by 0