1 citations · 3 across the 16 of their papers we have counts for
6 papers · 1 filter
MedEasy: Designing AI Standardized Patients for Clinical Consultation Training
Zhiqi Gao, Huarui Luo, Guo Zhu +6
AI standardized patients are becoming a setting for professional training in clinical consultation. This paper presents MedEasy, a multi-agent system that organizes virtual-patient…
NeuroWise: A Multi-Agent LLM "Glass-Box" System for Practicing Double-Empathy Communication with Autistic Partners
Albert Tang, Yifan Mo, Jie Li +5
The double empathy problem frames communication difficulties between neurodivergent and neurotypical individuals as arising from mutual misunderstanding, yet most interventions foc…
"It Talks Like a Patient, But Feels Different": Co-Designing AI Standardized Patients with Medical Learners
Zhiqi Gao, Guo Zhu, Huarui Luo +6
Standardized patients (SPs) play a central role in clinical communication training but are costly, difficult to scale, and inconsistent. Large language model (LLM) based AI standar…
Trustworthy AI Psychotherapy: Multi-Agent LLM Workflow for Counseling and Explainable Mental Disorder Diagnosis
Mithat Can Ozgun, Jiahuan Pei, Koen Hindriks +3
LLM-based agents have emerged as transformative tools capable of executing complex tasks through iterative planning and action, achieving significant advancements in understanding…
Talking-to-Build: How LLM-Assisted Interface Shapes Player Performance and Experience in Minecraft
Xin Sun, Lei Wang, Yue Li +5
With large language models (LLMs) on the rise, in-game interactions are shifting from rigid commands to natural conversations. However, the impacts of LLMs on player performance an…
Script-Strategy Aligned Generation: Aligning LLMs with Expert-Crafted Dialogue Scripts and Therapeutic Strategies for Psychotherapy
Xin Sun, Jan de Wit, Zhuying Li +3
Chatbots or conversational agents (CAs) are increasingly used to improve access to digital psychotherapy. Many current systems rely on rigid, rule-based designs, heavily dependent…