publications

2025

1. 

   Online Health Information–Seeking in the Era of Large Language Models: Cross-Sectional Web-Based Survey Study

   Hye Sun Yun, and Timothy Bickmore

   J Med Internet Res, Mar 2025

   DOI HTML PDF

2. 

   Framing Health Information: The Impact of Search Methods and Source Types on User Trust and Satisfaction in the Age of LLMs

   Hye Sun Yun, and Timothy Bickmore

   In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, Mar 2025

   DOI PDF Poster Slides
3. Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?

   Hye Sun Yun, Karen Y. C. Zhang, Ramez Kouzy, and 3 more authors

   Mar 2025

   PDF Code

2024

1. 

   Keeping Users Engaged During Repeated Interviews by a Virtual Agent: Using Large Language Models to Reliably Diversify Questions

   Hye Sun Yun, Mehdi Arjmand, Phillip Sherlock, and 3 more authors

   In Proceedings of the 24th ACM International Conference on Intelligent Virtual Agents, , Glasgow, United Kingdom, , Mar 2024

   DOI PDF Slides

2. 

   Investigating User Perceptions of Collaborative Agenda Setting in a Virtual Health Counseling Session

   Mina Fallah, Farnaz Nouraei, Hye Sun Yun, and 1 more author

   In Proceedings of the 24th ACM International Conference on Intelligent Virtual Agents, , Glasgow, United Kingdom, , Mar 2024

   DOI PDF

3. 

   Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models

   Hye Sun Yun, David Pogrebitskiy, Iain J Marshall, and 1 more author

   In Machine Learning for Healthcare Conference, Mar 2024

   PDF Code Poster

2023

1. 

   In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving

   Iain J. Marshall, Thomas A. Trikalinos, Frank Soboczenski, and 4 more authors

   Journal of Clinical Epidemiology, Mar 2023

   DOI HTML

2. 

   Improving Multiparty Interactions with a Robot Using Large Language Models

   Prasanth Murali, Ian Steenstra, Hye Sun Yun, and 2 more authors

   In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, Hamburg, Germany, Mar 2023

   Abs DOI PDF

   Speaker diarization is a key component of systems that support multiparty interactions of co-located users, such as meeting facilitation robots. The goal is to identify who spoke what, often to provide feedback, moderate participation, and personalize responses by the robot. Current systems use a combination of acoustic (e.g. pitch differences) and visual features (e.g. gaze) to perform diarization, but involve the use of additional sensors or require overhead signal processing efforts. Alternatively, automatic speech recognition (ASR) is a necessary step in the diarization pipeline, and utilizing the transcribed text to directly identify speaker labels in the conversation can eliminate such challenges. With that motivation, we leverage large language models (LLMs) to identify speaker labels from transcribed text and observe an exact match of 77% and a word level accuracy of 90%. We discuss our findings and the potential use of LLMs as a diarization tool for future systems.

3. 

   Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews

   Hye Sun Yun, Iain Marshall, Thomas Trikalinos, and 1 more author

   In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Mar 2023

   PDF Code Poster Slides Website

2022

1. 

   Techno-Spiritual Engagement: Mechanisms for Improving Uptake of mHealth Apps Designed for Church Members

   Hye Sun Yun, Shou Zhou, Everlyne Kimani, and 7 more authors

   In Joint Proceedings of the IUI 2022 Workshops: APEx-UI, HAI-GEN, HEALTHI, HUMANIZE, TExSS, SOCIALIZE co-located with the ACM International Conference on Intelligent User Interfaces (IUI 2022), Virtual Event, Helsinki, Finland, March 21-22, 2022, Mar 2022

   PDF Slides

2. 

   Church after Sunday: supporting everyday well-being through techno-spiritual health interventions

   Teresa K O’Leary, Elizabeth Stowell, Darley Sackitey, and 5 more authors

   Interactions, Mar 2022

   PDF

3. 

   Motivating Health Behavior Change with a Storytelling Virtual Agent

   Hye Sun Yun, Matias Volonte, and Timothy Bickmore

   In Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents, Faro, Portugal, Mar 2022

   Abs DOI PDF Poster

   We developed a virtual agent that motivates church-going users to change their health behavior by telling existing cultural narratives that have high relevance with the counseling topic in an engaging way. We evaluated this agent in a between-subjects experiment where participants interacted with an agent that counseled them on nutrition either without a story, with a story but told in a neutral speech style, or with a story using dramatic delivery inspired by church sermons. We found that interaction with either one of the storytelling agents leads to a significantly greater change in confidence to engage in the target behavior of healthy eating than interacting with a non-storytelling agent, demonstrating the efficacy of stories in health counseling by virtual agents.