6 papers
Eyes Can't Always Tell: Fusing Eye Tracking and User Priors for User Modeling under AI Advice Conditions
Xin Sun, Shu Wei, Ting Pan +5
Modeling users' cognitive states (e.g., cognitive load and decision confidence) is essential for building adaptive AI in high-stakes decision-making. While eye tracking provides no…
When LLM Rationales Become User-Facing: Effects on Trust Perception, Decision-Making, and Gaze Behaviors
Xin Sun, Ting Pan, Yajing Wang +5
Large language models (LLMs) increasingly show step-by-step reasoning rationales alongside their answers, turning reasoning from an internal model capability into a user-facing int…
Trust Stack for Mental Health AI: A Survey of Calibration across Human, Interaction, and AI Layers
Xin Sun, Yue Su, Yifan Mo +9
Language-based AI is increasingly deployed for mental health support, yet trust is evaluated in interdisciplinary but operationally misaligned ways: NLP and AI work measures robust…
Understanding Trust Toward Human versus AI-generated Health Information through Behavioral and Physiological Sensing
Xin Sun, Rongjun Ma, Shu Wei +3
As AI-generated health information proliferates online and becomes increasingly indistinguishable from human-sourced information, it becomes critical to understand how people trust…
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…
Rethinking the Alignment of Psychotherapy Dialogue Generation with Motivational Interviewing Strategies
Xin Sun, Xiao Tang, Abdallah El Ali +5
Recent advancements in large language models (LLMs) have shown promise in generating psychotherapeutic dialogues, particularly in the context of motivational interviewing (MI). How…