In the field of psychology, traditional assessment methods, such as standardized scales, are frequently critiqued for their static nature, lack of personalization, and reduced participant engagement, while comprehensive counseling evaluations are often inaccessible. The complexity of quantifying psychological traits further limits these methods. Despite advances with large language models (LLMs), many still depend on single-round Question-and-Answer interactions. To bridge this gap, we introduce PsyDI, a personalized and progressively in-depth chatbot designed for psychological measurements, exemplified by its application in the Myers-Briggs Type Indicator (MBTI) framework. PsyDI leverages user-related multi-modal information and engages in customized, multi-turn interactions to provide personalized, easily accessible measurements, while ensuring precise MBTI type determination. To address the challenge of unquantifiable psychological traits, we introduce a novel training paradigm that involves learning the ranking of proxy variables associated with these traits, culminating in a robust score model for MBTI measurements. The score model enables PsyDI to conduct comprehensive and precise measurements through multi-turn interactions within a unified estimation context. Through various experiments, we validate the efficacy of both the score model and the PsyDI pipeline, demonstrating its potential to serve as a general framework for psychological measurements. Furthermore, the online deployment of PsyDI has garnered substantial user engagement, with over 3,000 visits, resulting in the collection of numerous multi-turn dialogues annotated with MBTI types, which facilitates further research. The source code for the training and web service components is publicly available as a part of OpenDILab at: https://github.com/opendilab/PsyDI
Characterizing Delusional Spirals through Human-LLM Chat Logs
Stanford University（斯坦福大学）；Carnegie Mellon University（卡内基梅隆大学）；University of Chicago（芝加哥大学）；Independent Researcher（独立研究者）；Harvard Belfer Center（哈佛贝尔弗中心）；University of Minnesota（明尼苏达大学）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）
MoPHES:Leveraging on-device LLMs as Agent for Mobile Psychological Health Evaluation and Support
School of Software Engineering, Jiangxi University of Science and Technology（江西科技理工大学软件工程学院）；School of Computer Science, Shenzhen University（深圳大学计算机科学学院）
PsychAdapter: Adapting LLM Transformers to Reflect Traits, Personality and Mental Health
Stony Brook University（石溪大学）；New York University（纽约大学）；University of Melbourne（墨尔本大学）；University of Texas at Dallas（德克萨斯大学达拉斯分校）；University of Pennsylvania（宾夕法尼亚大学）；Stanford University（斯坦福大学）
XInsight: Integrative Stage-Consistent Psychological Counseling Support Agents for Digital Well-Being
Hefei University of Technology（合肥工业大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）；Anhui University（安徽大学）；United Arab Emirates University（阿联酋大学）；Intelligent Interconnected Systems Laboratory of Anhui Province (HFUT)（安徽省智能互联系统实验室（HFUT））
A clinically validated framework for auditing AI chatbot behavior in mental health interactions
Max Planck UCL Centre for Computational Psychiatry and Ageing Research（马克斯·普朗克-伦敦大学学院计算精神病学与老龄化研究中心）；Sydney Medical School, University of Sydney（悉尼大学悉尼医学院）；UK AI Security Institute（英国人工智能安全研究所）；Department of Experimental Psychology, University of Oxford（牛津大学实验心理学系）；Microsoft AI（微软人工智能）；Department of Psychiatry, University of Oxford（牛津大学精神病学系）
When Chatbots Accommodate: Auditing the Response Policies of AI Companions in Vulnerable Conversations
USC Information Sciences Institute（南加州大学信息科学研究所）；Viterbi School of Engineering, USC（南加州大学维特比工程学院）；Annenberg School for Communication and Journalism, USC（南加州大学安嫩伯格传播与新闻学院）
EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety
Department of Electrical & Computer Engineering, Princeton University（普林斯顿大学电气与计算机工程系）；Department of Computer Science, Princeton University（普林斯顿大学计算机科学系）；Department of Computer Science & Engineering, University of Michigan（密歇根大学计算机科学与工程系）；Department of Data Science & Engineering, University of Michigan（密歇根大学数据科学与工程系）；Department of Philosophy, Columbia University（哥伦比亚大学哲学系）；AI Lab, Princeton University（普林斯顿大学人工智能实验室）；Chen Frontier Lab for Al and Mental Health, Tianqiao and Chrissy Chen Institute（天桥及克里斯西·陈研究所人工智能与心理健康前沿实验室）；Theta Health Inc.（Theta健康公司）
