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20242026
most citedTrusting the Search: Unraveling Human Trust in Health Information from Google and ChatGPT

13 citations · 15 across the 10 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.HC2026

From Search Agents to Dissemination Interfaces: Understanding Human Trust in Health Information from Conversational Search

Xin Sun, Rongjun Ma, Xiaochang Zhao +5

Large Language Models (LLMs) deployed through Conversational User Interfaces (CUIs) are transforming health information-seeking by offering immediate, interactive experiences compa…

cs.AI2026

When Trust Meets Truth: Trust-Truth Separability in LLM-as-Judge

Xin Sun, Di Wu, Yuchen Guo +4

LLM-as-Judge systems can produce multi-dimensional evaluations, such as trustworthiness, reliability, and factuality, and these outputs are often interpreted as independent evidenc…

cs.HC2026

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…

cs.CL2026

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…

cs.HC2026

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…