Chaoran Chen

schoolUniversity of Notre Damebar_chart#1048 Global Rank

Total Papers

HCI Rank

#1048

Research Areas

Years Active

Recent Publications

The Behavioral Fabric of LLM-Powered GUI Agents: Human Values and Interaction Outcomes

Large Language Model (LLM)-powered web GUI agents are increasingly automating everyday online tasks. Despite their popularity, little is known about how users' preferences and values impact agents' reasoning and behavior. In this work, we investigate how both explicit and implicit user preferences, as well as the unde…

CHI '262nd AuthorDark Patterns Recognition +3

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight

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 tasks from high-level intents, understanding how dark patterns affect agents is incr…

CHI '263rd AuthorHuman-LLM Collaboration +2

Through the Lens of Human-Human Collaboration: An Configurable Research Platform for Exploring Human-Agent Collaboration

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 opportunities for human-LLM-agent collaboration by enabling natural communication and va…

CHI '262nd AuthorHonorable MentionIntelligent Voice Assistants (Alexa, Siri, etc.) +3

My Favorite Streamer is an LLM: Discovering, Bonding, and Co-Creating in AI VTuber Fandom

AI VTubers, where the performer is not human but algorithmically generated, introduce a new context for fandom. While human VTubers have been substantially studied for their cultural appeal, parasocial dynamics, and community economies, little is known about how audiences engage with their AI counterparts. To address…

UIST '251st AuthorExplainable AI (XAI) +2

Why am I seeing this: Democratizing End User Auditing for Online Content Recommendations

Personalized recommendation systems tailor content based on user attributes, which are either provided or inferred from private data. Research suggests that users often hypothesize about reasons behind contents they encounter (e.g., ``I see this jewelry ad because I am a woman''), but they lack the means to confirm th…

IUI '251st AuthorGenerative AI (Text, Image, Music, Video) +3

CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applications

The rise of end-user applications powered by large language models (LLMs), including both conversational interfaces and add-ons to existing graphical user interfaces (GUIs), introduces new privacy challenges. However, many users remain unaware of the risks. This paper explores methods to increase user awareness of pri…

CHI '241st AuthorExplainable AI (XAI) +2

An Empathy-Based Sandbox Approach to Bridge the Privacy Gap among Attitudes, Goals, Knowledge, and Behaviors

Managing privacy to reach privacy goals is challenging, as evidenced by the privacy attitude-behavior gap. Mitigating this discrepancy requires solutions that account for both system opaqueness and users' hesitations in testing different privacy settings due to fears of unintended data exposure. We introduce an empath…

UIST '225th+ AuthorAR Navigation & Context Awareness

ARDW: An Augmented Reality Workbench for Printed Circuit Board Debugging

Debugging printed circuit boards (PCBs) can be a time-consuming process, requiring frequent context switching between PCB design files (schematic and layout) and the physical PCB. To assist electrical engineers in debugging PCBs, we present ARDW, an augmented reality workbench consisting of a monitor interface featuri…

CHI '213rd AuthorContext-Aware Computing +1

Patterns for Representing Knowledge Graphs to Communicate Situational Knowledge of Service Robots

Service robots are envisioned to be adaptive to their working environment based on situational knowledge. Recent research focused on designing visual representation of knowledge graphs for expert users. However, how to generate an understandable interface for non-expert users remains to be explored. In this paper, we…

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