Bingsheng Yao
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View article: "Mango Mango, How to Let The Lettuce Dry Without A Spinner?": Exploring User Perceptions of Using An LLM-Based Conversational Assistant Toward Cooking Partner
"Mango Mango, How to Let The Lettuce Dry Without A Spinner?": Exploring User Perceptions of Using An LLM-Based Conversational Assistant Toward Cooking Partner Open
The rapid advancement of Large Language Models (LLMs) has created numerous potentials for integration with conversational assistants (CAs) assisting people in their daily tasks, particularly due to their extensive flexibility. However, use…
View article: Exploring Collaboration Breakdowns Between Provider Teams and Patients in Post-Surgery Care
Exploring Collaboration Breakdowns Between Provider Teams and Patients in Post-Surgery Care Open
Post-surgery care involves ongoing collaboration between provider teams and patients, which starts from post-surgery hospitalization through home recovery after discharge. While prior HCI research has primarily examined patients' challenge…
View article: Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration
Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration Open
Intelligent systems have traditionally been designed as tools rather than collaborators, often lacking critical characteristics that collaboration partnerships require. Recent advances in large language model (LLM) agents open new opportun…
View article: Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight Open
The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate task…
View article: Vital Insight: Assisting Experts' Context-Driven Sensemaking of Multi-modal Personal Tracking Data Using Visualization and Human-in-the-Loop LLM
Vital Insight: Assisting Experts' Context-Driven Sensemaking of Multi-modal Personal Tracking Data Using Visualization and Human-in-the-Loop LLM Open
Passive tracking methods, such as phone and wearable sensing, have become dominant in monitoring human behaviors in modern ubiquitous computing studies. While there have been significant advances in machine-learning approaches to translate…
View article: SurgWound-Bench: A Benchmark for Surgical Wound Diagnosis
SurgWound-Bench: A Benchmark for Surgical Wound Diagnosis Open
Surgical site infection (SSI) is one of the most common and costly healthcare-associated infections and and surgical wound care remains a significant clinical challenge in preventing SSIs and improving patient outcomes. While recent studie…
View article: Designing AI Tools for Clinical Care Teams to Support Serious Illness Conversations with Older Adults in the Emergency Department
Designing AI Tools for Clinical Care Teams to Support Serious Illness Conversations with Older Adults in the Emergency Department Open
Serious illness conversations (SICs), discussions between clinical care teams and patients with serious, life-limiting illnesses about their values, goals, and care preferences, are critical for patient-centered care. Without these convers…
View article: CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Prediction of Cancer Treatment-Induced Cardiotoxicity
CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Prediction of Cancer Treatment-Induced Cardiotoxicity Open
Despite recent advances in cancer treatments that prolong patients' lives, treatment-induced cardiotoxicity (i.e., the various heart damages caused by cancer treatments) emerges as one major side effect. The clinical decision-making proces…
View article: Characterizing LLM-Empowered Personalized Story Reading and Interaction for Children: Insights From Multi-Stakeholder Perspectives
Characterizing LLM-Empowered Personalized Story Reading and Interaction for Children: Insights From Multi-Stakeholder Perspectives Open
Personalized interaction is highly valued by parents in their story-reading activities with children. While AI-empowered story-reading tools have been increasingly used, their abilities to support personalized interaction with children are…
View article: Examining Student and Teacher Perspectives on Undisclosed Use of Generative AI in Academic Work
Examining Student and Teacher Perspectives on Undisclosed Use of Generative AI in Academic Work Open
View article: AgentA/B: Automated and Scalable Web A/BTesting with Interactive LLM Agents
AgentA/B: Automated and Scalable Web A/BTesting with Interactive LLM Agents Open
A/B testing experiment is a widely adopted method for evaluating UI/UX design decisions in modern web applications. Yet, traditional A/B testing remains constrained by its dependence on the large-scale and live traffic of human participant…
View article: SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction
SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction Open
Sepsis is an organ dysfunction caused by a deregulated immune response to an infection. Early sepsis prediction and identification allow for timely intervention, leading to improved clinical outcomes. Clinical calculators (e.g., the…
View article: Can LLM Agents Simulate Multi-Turn Human Behavior? Evidence from Real Online Customer Behavior Data
Can LLM Agents Simulate Multi-Turn Human Behavior? Evidence from Real Online Customer Behavior Data Open
Recent research shows that LLM Agents can generate ``believable'' human behaviors via prompt-only methods, and such agents have been increasingly adopted in downstream applications. However, existing evaluation of these agents only focuses…
View article: UXAgent: An LLM Agent-Based Usability Testing Framework for Web Design
UXAgent: An LLM Agent-Based Usability Testing Framework for Web Design Open
Usability testing is a fundamental yet challenging (e.g., inflexible to iterate the study design flaws and hard to recruit study participants) research method for user experience (UX) researchers to evaluate a web design. Recent advances i…
View article: WatchGuardian: Enabling User-Defined Personalized Just-in-Time Intervention on Smartwatch
WatchGuardian: Enabling User-Defined Personalized Just-in-Time Intervention on Smartwatch Open
While just-in-time interventions (JITIs) have effectively targeted common health behaviors, individuals often have unique needs to intervene in personal undesirable actions that can negatively affect physical, mental, and social well-being…
View article: RECOVER: Designing a Large Language Model-based Remote Patient Monitoring System for Postoperative Gastrointestinal Cancer Care
RECOVER: Designing a Large Language Model-based Remote Patient Monitoring System for Postoperative Gastrointestinal Cancer Care Open
Cancer surgery is a key treatment for gastrointestinal (GI) cancers, a group of cancers that account for more than 35% of cancer-related deaths worldwide, but postoperative complications are unpredictable and can be life-threatening. In th…
View article: "It Felt Like I Was Left in the Dark": Exploring Information Needs and Design Opportunities for Family Caregivers of Older Adult Patients in Critical Care Settings
"It Felt Like I Was Left in the Dark": Exploring Information Needs and Design Opportunities for Family Caregivers of Older Adult Patients in Critical Care Settings Open
Older adult patients constitute a rapidly growing subgroup of Intensive Care Unit (ICU) patients. In these situations, their family caregivers are expected to represent the unconscious patients to access and interpret patients' medical inf…
View article: More Modality, More AI: Exploring Design Opportunities of AI-Based Multi-modal Remote Monitoring Technologies for Early Detection of Mental Health Sequelae in Youth Concussion Patients
More Modality, More AI: Exploring Design Opportunities of AI-Based Multi-modal Remote Monitoring Technologies for Early Detection of Mental Health Sequelae in Youth Concussion Patients Open
Anxiety, depression, and suicidality are common mental health sequelae following concussion in youth patients, often exacerbating concussion symptoms and prolonging recovery. Despite the critical need for early detection of these mental he…
View article: Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction
Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction Open
Recent advances in large language models (LLMs) have shown potential in clinical text summarization, but their ability to handle long patient trajectories with multi-modal data spread across time remains underexplored. This study systemati…
View article: Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction
Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Prediction Open
View article: SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction
SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction Open
Sepsis is an organ dysfunction caused by a deregulated immune response to an infection. Early sepsis prediction and identification allow for timely intervention, leading to improved clinical outcomes. Clinical calculators (e.g., the six-or…
View article: LLMs are Imperfect, Then What? An Empirical Study on LLM Failures in Software Engineering
LLMs are Imperfect, Then What? An Empirical Study on LLM Failures in Software Engineering Open
Software engineers are integrating AI assistants into their workflows to enhance productivity and reduce cognitive strain. However, experiences vary significantly, with some engineers finding large language models (LLMs), like ChatGPT, ben…
View article: Challenges and Opportunities of LLM-Based Synthetic Personae and Data in HCI
Challenges and Opportunities of LLM-Based Synthetic Personae and Data in HCI Open
View article: Understanding the Daily Lives of Older Adults: Integrating Multi-modal Personal Health Tracking Data through Visualization and Large Language Models
Understanding the Daily Lives of Older Adults: Integrating Multi-modal Personal Health Tracking Data through Visualization and Large Language Models Open
Understanding the daily lives and routines of older adults is crucial to facilitate aging in place. Ubiquitous computing technologies like smartphones and wearables that are easy to deploy and scale, have become a popular method to collect…
View article: Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model
Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model Open
Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication methods, which suffer from limited availability, informatio…
View article: Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Interactive Storytelling and Reading Activities
Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Interactive Storytelling and Reading Activities Open
Interactive storytelling is vital for preschooler development. While children's interactive partners have traditionally been their parents and teachers, recent advances in artificial intelligence (AI) have sparked a surge of AI-based story…
View article: Vital Insight: Assisting Experts' Context-Driven Sensemaking of Multi-modal Personal Tracking Data Using Visualization and Human-In-The-Loop LLM
Vital Insight: Assisting Experts' Context-Driven Sensemaking of Multi-modal Personal Tracking Data Using Visualization and Human-In-The-Loop LLM Open
Passive tracking methods, such as phone and wearable sensing, have become dominant in monitoring human behaviors in modern ubiquitous computing studies. While there have been significant advances in machine-learning approaches to translate…
View article: CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Detection of Cancer Treatment-Induced Cardiotoxicity
CardioAI: A Multimodal AI-based System to Support Symptom Monitoring and Risk Detection of Cancer Treatment-Induced Cardiotoxicity Open
Despite recent advances in cancer treatments that prolong patients' lives, treatment-induced cardiotoxicity remains one severe side effect. The clinical decision-making of cardiotoxicity is challenging, as non-clinical symptoms can be miss…
View article: Why Interdisciplinary Teams Fail: A Systematic Analysis With Activity Theory in Clinical AI Collaboration
Why Interdisciplinary Teams Fail: A Systematic Analysis With Activity Theory in Clinical AI Collaboration Open
Advanced AI technologies are increasingly integrated into clinical domains to advance patient care. The design and development of clinical AI technologies necessitate seamless collaboration between clinical and technical experts. Yet, such…
View article: Secret Use of Large Language Model (LLM)
Secret Use of Large Language Model (LLM) Open
The advancements of Large Language Models (LLMs) have decentralized the responsibility for the transparency of AI usage. Specifically, LLM users are now encouraged or required to disclose the use of LLM-generated content for varied types o…