5 citations · 16 across the 10 of their papers we have counts for
10 papers
PsychePass: Calibrating LLM Therapeutic Competence via Trajectory-Anchored Tournaments
Zhuang Chen, Dazhen Wan, Zhangkai Zheng +4
While large language models show promise in mental healthcare, evaluating their therapeutic competence remains challenging due to the unstructured and longitudinal nature of counse…
Unveiling the Landscape of Clinical Depression Assessment: From Behavioral Signatures to Psychiatric Reasoning
Zhuang Chen, Guanqun Bi, Wen Zhang +5
Depression is a widespread mental disorder that affects millions worldwide. While automated depression assessment shows promise, most studies rely on limited or non-clinically vali…
Reframe Your Life Story: Interactive Narrative Therapist and Innovative Moment Assessment with Large Language Models
Yi Feng, Jiaqi Wang, Wenxuan Zhang +6
Recent progress in large language models (LLMs) has opened new possibilities for mental health support, yet current approaches lack realism in simulating specialized psychotherapy…
SocialSim: Towards Socialized Simulation of Emotional Support Conversation
Zhuang Chen, Yaru Cao, Guanqun Bi +6
Emotional support conversation (ESC) helps reduce people's psychological stress and provide emotional value through interactive dialogues. Due to the high cost of crowdsourcing a l…
Ψ-Arena: Interactive Assessment and Optimization of LLM-based Psychological Counselors with Tripartite Feedback
Shijing Zhu, Zhuang Chen, Guanqun Bi +10
Large language models (LLMs) have shown promise in providing scalable mental health support, while evaluating their counseling capability remains crucial to ensure both efficacy an…
MAGI: Multi-Agent Guided Interview for Psychiatric Assessment
Guanqun Bi, Zhuang Chen, Zhoufu Liu +9
Automating structured clinical interviews could revolutionize mental healthcare accessibility, yet existing large language models (LLMs) approaches fail to align with psychiatric d…
Enhanced Large Language Models for Effective Screening of Depression and Anxiety
June M. Liu, Mengxia Gao, Sahand Sabour +3
Depressive and anxiety disorders are widespread, necessitating timely identification and management. Recent advances in Large Language Models (LLMs) offer potential solutions, yet…
CharacterBench: Benchmarking Character Customization of Large Language Models
Jinfeng Zhou, Yongkang Huang, Bosi Wen +13
Character-based dialogue (aka role-playing) enables users to freely customize characters for interaction, which often relies on LLMs, raising the need to evaluate LLMs' character c…
ToMBench: Benchmarking Theory of Mind in Large Language Models
Zhuang Chen, Jincenzi Wu, Jinfeng Zhou +8
Theory of Mind (ToM) is the cognitive capability to perceive and ascribe mental states to oneself and others. Recent research has sparked a debate over whether large language model…
CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models
Jinfeng Zhou, Zhuang Chen, Dazhen Wan +14
In this paper, we present CharacterGLM, a series of models built upon ChatGLM, with model sizes ranging from 6B to 66B parameters. Our CharacterGLM is designed for generating Chara…