# ChatCounselor: A Large Language Models for Mental Health Support

arXiv: https://arxiv.org/abs/2309.15461 · HTML: https://mlsanity.com/paper/2309.15461/

## Key facts

- Cited by 44 papers in the map (data through 14 Oct 2026).
- Builds on 26 of its 42 references that are in the map.
- First posted on arXiv 27 Sep 2023.

## Builds on (most cited first, 26 of 26)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams](https://mlsanity.com/paper/2009.13081/) (2020)
- [PubMedQA: A Dataset for Biomedical Research Question Answering](https://mlsanity.com/paper/1909.06146/) (2019)
- [GLM: General Language Model Pretraining with Autoregressive Blank Infilling](https://mlsanity.com/paper/2103.10360/) (2021)
- [BloombergGPT: A Large Language Model for Finance](https://mlsanity.com/paper/2303.17564/) (2023)
- [Training Deep Nets with Sublinear Memory Cost](https://mlsanity.com/paper/1604.06174/) (2016)
- [LaMP: When Large Language Models Meet Personalization](https://mlsanity.com/paper/2304.11406/) (2023)
- [ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge](https://mlsanity.com/paper/2303.14070/) (2023)
- [Large Language Models are Zero-Shot Rankers for Recommender Systems](https://mlsanity.com/paper/2305.08845/) (2023)
- [Towards Emotional Support Dialog Systems](https://mlsanity.com/paper/2106.01144/) (2021)
- [HuatuoGPT, towards Taming Language Model to Be a Doctor](https://mlsanity.com/paper/2305.15075/) (2023)
- [Large Language Models as Zero-Shot Conversational Recommenders](https://mlsanity.com/paper/2308.10053/) (2023)
- [PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support](https://mlsanity.com/paper/2106.01702/) (2021)
- [ChatGPT: The End of Online Exam Integrity?](https://mlsanity.com/paper/2212.09292/) (2022)
- [LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models](https://mlsanity.com/paper/2306.12420/) (2023)
- [On the Educational Impact of ChatGPT: Is Artificial Intelligence Ready to Obtain a University Degree?](https://mlsanity.com/paper/2303.11146/) (2023)
- [A Brief Report on LawGPT 1.0: A Virtual Legal Assistant Based on GPT-3](https://mlsanity.com/paper/2302.05729/) (2023)
- [SMILE: Single-turn to Multi-turn Inclusive Language Expansion via ChatGPT for Mental Health Support](https://mlsanity.com/paper/2305.00450/) (2023)
- [PAL: Persona-Augmented Emotional Support Conversation Generation](https://mlsanity.com/paper/2212.09235/) (2022)
- [Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Models](https://mlsanity.com/paper/2307.11991/) (2023)
- [Mind meets machine: Unravelling GPT-4's cognitive psychology](https://mlsanity.com/paper/2303.11436/) (2023)
- [Zero-Shot Recommendation as Language Modeling](https://mlsanity.com/paper/2112.04184/) (2021)
- [Enhancing Psychological Counseling with Large Language Model: A Multifaceted Decision-Support System for Non-Professionals](https://mlsanity.com/paper/2308.15192/) (2023)
- [CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation](https://mlsanity.com/paper/2208.08845/) (2022)
- [A Benchmark for Understanding Dialogue Safety in Mental Health Support](https://mlsanity.com/paper/2307.16457/) (2023)

## Built on by (most cited first, 30 of 44)

- [A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily](https://mlsanity.com/paper/2311.08268/) (2023)
- [A Survey of Large Language Models in Medicine: Progress, Application, and Challenge](https://mlsanity.com/paper/2311.05112/) (2023)
- [A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicine](https://mlsanity.com/paper/2405.08603/) (2024)
- [Large Language Models in Mental Health Care: a Scoping Review](https://mlsanity.com/paper/2401.02984/) (2024)
- [RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents](https://mlsanity.com/paper/2507.03112/) (2025)
- [Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contexts](https://mlsanity.com/paper/2403.13786/) (2024)
- [Beyond Empathy: Integrating Diagnostic and Therapeutic Reasoning with Large Language Models for Mental Health Counseling](https://mlsanity.com/paper/2505.15715/) (2025)
- [Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review](https://mlsanity.com/paper/2401.01519/) (2024)
- [Large Language Model Benchmarks in Medical Tasks](https://mlsanity.com/paper/2410.21348/) (2024)
- [Rethinking Large Language Models in Mental Health Applications](https://mlsanity.com/paper/2311.11267/) (2023)
- [ERD: A Framework for Improving LLM Reasoning for Cognitive Distortion Classification](https://mlsanity.com/paper/2403.14255/) (2024)
- [PsyEval: A Suite of Mental Health Related Tasks for Evaluating Large Language Models](https://mlsanity.com/paper/2311.09189/) (2023)
- [PsyChat: A Client-Centric Dialogue System for Mental Health Support](https://mlsanity.com/paper/2312.04262/) (2023)
- [Preference Learning Unlocks LLMs' Psycho-Counseling Skills](https://mlsanity.com/paper/2502.19731/) (2025)
- [Prefill-level Jailbreak: A Black-Box Risk Analysis of Large Language Models](https://mlsanity.com/paper/2504.21038/) (2025)
- [Response Generation for Cognitive Behavioral Therapy with Large Language Models: Comparative Study with Socratic Questioning](https://mlsanity.com/paper/2401.15966/) (2024)
- [Structured Dialogue System for Mental Health: An LLM Chatbot Leveraging the PM+ Guidelines](https://mlsanity.com/paper/2411.10681/) (2024)
- [HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents](https://mlsanity.com/paper/2502.05982/) (2025)
- [Between Help and Harm: An Evaluation of Mental Health Crisis Handling by LLMs](https://mlsanity.com/paper/2509.24857/) (2025)
- [Evolution of meta's llama models and parameter-efficient fine-tuning of large language models: a survey](https://mlsanity.com/paper/2510.12178/) (2025)
- [Bioinformatics and Biomedical Informatics with ChatGPT: Year One Review](https://mlsanity.com/paper/2403.15274/) (2024)
- [Implicit Turn-Wise Policy Optimization for Proactive User-LLM Interaction](https://mlsanity.com/paper/2603.23550/) (2026)
- [Enhancing Psychotherapy Counseling: A Data Augmentation Pipeline Leveraging Large Language Models for Counseling Conversations](https://mlsanity.com/paper/2406.08718/) (2024)
- [TRUST: An LLM-Based Dialogue System for Trauma Understanding and Structured Assessments](https://mlsanity.com/paper/2504.21851/) (2025)
- [A Comprehensive Review of Datasets for Clinical Mental Health AI Systems](https://mlsanity.com/paper/2508.09809/) (2025)
- [PsychAgent: An Experience-Driven Lifelong Learning Agent for Self-Evolving Psychological Counselor](https://mlsanity.com/paper/2604.00931/) (2026)
- [Optimizing Psychological Counseling with Instruction-Tuned Large Language Models](https://mlsanity.com/paper/2406.13617/) (2024)
- [It Hears, It Sees too: Multi-Modal LLM for Depression Detection By Integrating Visual Understanding into Audio Language Models](https://mlsanity.com/paper/2511.19877/) (2025)
- [SOS-1K: A Fine-grained Suicide Risk Classification Dataset for Chinese Social Media Analysis](https://mlsanity.com/paper/2404.12659/) (2024)
- [Evaluating the Effectiveness of the Foundational Models for Q&A Classification in Mental Health care](https://mlsanity.com/paper/2406.15966/) (2024)

## Abstract (arXiv)

This paper presents ChatCounselor, a large language model (LLM) solution designed to provide mental health support. Unlike generic chatbots, ChatCounselor is distinguished by its foundation in real conversations between consulting clients and professional psychologists, enabling it to possess specialized knowledge and counseling skills in the field of psychology. The training dataset, Psych8k, was constructed from 260 in-depth interviews, each spanning an hour. To assess the quality of counseling responses, the counseling Bench was devised. Leveraging GPT-4 and meticulously crafted prompts based on seven metrics of psychological counseling assessment, the model underwent evaluation using a set of real-world counseling questions. Impressively, ChatCounselor surpasses existing open-source models in the counseling Bench and approaches the performance level of ChatGPT, showcasing the remarkable enhancement in model capability attained through high-quality domain-specific data.