activity
20232026
most citedMindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention

40 citations · 40 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026

U-Lens: Supporting User Uncertainty Management in Long-Form LLM Responses

Yu Mei, Qingyue Zhuang, Jie Cai +5

Uncertainty can appear throughout LLM-generated text (e.g., questionable claims, ambiguous terms). Prior work largely focuses on making such uncertainty visible through cues such a…

cs.AI2026

STRIDE: Strategic Iterative Decision-Making for Retrieval-Augmented Multi-Hop Question Answering

Wei Chen, Lili Zhao, Zhi Zheng +2

Multi-hop question answering (MHQA) enables accurate answers to complex queries by retrieving and reasoning over evidence dispersed across multiple documents. Existing MHQA approac…

cs.HC2026

Intelligent Drill-Down: Large Language Model-Driven Drill-Down Technique for Human-AI Collaborative Visual Exploration

Zhijun Zheng, Tian Qiu, Yuheng Zhao +1

In visual analytics, applying filters to drill-down and extract higher-value insights is a common and important data analysis method. When the drill-down space becomes excessively…

cs.HC2025

TextOnly: A Unified Function Portal for Text-Related Functions on Smartphones

Minghao Tu, Chun Yu, Xiyuan Shen +3

Text boxes serve as portals to diverse functionalities in today's smartphone applications. However, when it comes to specific functionalities, users always need to navigate through…

cs.CL2023★ 40 cited

MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention

Ruolan Wu, Chun Yu, Xiaole Pan +9

Problematic smartphone use negatively affects physical and mental health. Despite the wide range of prior research, existing persuasive techniques are not flexible enough to provid…