Large language models (LLMs) have shown promise for mental health support, yet training such models is constrained by the scarcity and sensitivity of real counseling dialogues. In this article, we present MindChat, a privacy-preserving LLM for mental health support, together with MindCorpus, a synthetic multi-turn counseling dataset constructed via a multi-agent role-playing framework. To synthesize high-quality counseling data, the developed dialogue-construction framework employs a dual closed-loop feedback design to integrate psychological expertise and counseling techniques through role-playing: (i) turn-level critique-and-revision to improve coherence and counseling appropriateness within a session, and (ii) session-level strategy refinement to progressively enrich counselor behaviors across sessions. To mitigate privacy risks under decentralized data ownership, we fine-tune the base model using federated learning with parameter-efficient LoRA adapters and incorporate differentially private optimization to reduce membership and memorization risks. Experiments on synthetic-data quality assessment and counseling capability evaluation show that MindCorpus improves training effectiveness and that MindChat is competitive with existing general and counseling-oriented LLM baselines under both automatic LLM-judge and human evaluation protocols, while exhibiting reduced privacy leakage under membership inference attacks.
ProMind-LLM: Proactive Mental Health Care via Causal Reasoning with Sensor Data
California Institute of Technology（加州理工学院）；UCLA（加州大学洛杉矶分校）；National University of Singapore（新加坡国立大学）；Hangzhou Dianzi University（杭州电子科技大学）；Fudan University（复旦大学）
TrustMH-Bench: A Comprehensive Benchmark for Evaluating the Trustworthiness of Large Language Models in Mental Health
Renmin University of China, China（中国人民大学）；Beijing University of Posts and Telecommunications, China（北京邮电大学）；Hefei University of Technology, China（合肥工业大学）
A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMs
Center for Advanced Internet Studies Bochum Germany；Center for Advanced Internet Studies \& University of Wuppertal Bochum Germany；Center for Advanced Internet Studies；Center for Advanced Internet Studies \& University of Wuppertal
Helen Wills Neuroscience Institute, University of California Berkeley, USA（加州大学伯克利分校海伦·威尔斯神经科学研究所）；Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK（马克斯·普朗克伦敦大学学院计算精神病学与衰老研究中心）；Department of Psychology, University of California Berkeley, USA（加州大学伯克利分校心理学系）；Vision Science Group, University of California Berkeley, USA（加州大学伯克利分校视觉科学组）
Can Artificial Intelligence Support Healthcare and Mental Health Through Early Cyberbullying Detection ? The Impact of Emotion-Aware AI on Proactive Online Safety
Faculty of Computer Science, University of New Brunswick（新不伦瑞克大学计算机科学学院）；Khoury College of Computer Sciences, Northeastern University（东北大学库里计算机科学学院）
Towards Privacy-aware Mental Health AI Models: Advances, Challenges, and Opportunities
Ubiquitous Knowledge Processing Lab (UKP Lab) Department of Computer Science and Hessian Center for AI (hessian.AI) Technische Universität Darmstadt National Research Center for Applied Cybersecurity ATHENE, Germany（技术大学达姆施塔特应用网络安全国家研究中心、海森国家人工智能中心（hessian.AI）、计算机科学系、无处不在知识处理实验室（UKP Lab））；Department of Electrical Engineering, Indian Institute of Technology Delhi, India（印度德里印度理工学院电气工程系）；Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, India（印度德里印度理工学院人工智能学院）
The Cost-Benefit of Interdisciplinarity in AI for Mental Health
Center for Social Data Science, Faculty of Social Sciences, University of Copenhagen（哥本哈根大学社会科学学院社会数据科学中心）；Dept. of Applied Mathematics and Computer Science, Technical University of Denmark（丹麦技术大学应用数学与计算机科学系）；Institute for Ethics in Artificial Intelligence, School of Social Sciences and Technology, Technical University of Munich（慕尼黑技术大学社会科学与技术学院人工智能伦理研究所）；Dept. of Mathematical Sciences, University of Copenhagen（哥本哈根大学数学科学系）；Child and Adolescent Mental Health Center, Copenhagen University Hospital（哥本哈根大学医院青少年与儿童心理健康中心）
Quantifying Mental Health from Social Media with Neural User Embeddings
INESC-ID Lisboa（里斯本INESC-ID研究所）；Instituto Superior Técnico（高等技术学院）；Universidade de Lisboa（里斯本大学）；Qntfy（Qntfy公司）；Universidade Europeia（欧洲大学）；Northeastern University（东北大学）
A Checklist for Trustworthy, Safe, and User-Friendly Mental Health Chatbots
University of Illinois Urbana-Champaign, Urbana, United States（伊利诺伊大学厄巴纳-香槟分校）；Indiana University Indianapolis, Indianapolis, United States（印第安纳大学印第安纳波利斯分校）
Seeking Late Night Life Lines: Experiences of Conversational AI Use in Mental Health Crisis
University of Minnesota（明尼苏达大学）；Northwestern University（西北大学）；Dartmouth College（达特茅斯学院）；Microsoft（微软）；Mental Health America（心理健康美国）；Microsoft Research（微软研究院）
An Offline Mobile Conversational Agent for Mental Health Support: Learning from Emotional Dialogues and Psychological Texts with Student-Centered Evaluation
Department of Electrical Engineering and Computer Science, Indian Institute of Science Education and Research Bhopal（电子工程与计算机科学系，比哈尔印度科学教育与研究中心）
