24 citations · 25 across the 10 of their papers we have counts for
13 papers
Beyond Oracle Communication: Benchmarking Interactive Intent Alignment Under Miscommunication and Evolving User Intent
Zheyuan Zhang, Mengyuan Chao, Ke Xiao +5
Modern LLM agents increasingly tackle complex tasks through interactive, long-horizon exchanges with users, while existing benchmarks generally assume that users always accurately…
UXBench: Measuring the Actionability of LLM-Generated UX Critiques
Wenjie Wang, Yue Huang, Zipeng Ling +11
Large language models (LLMs) are increasingly deployed as UX judges that inspect interfaces, diagnose usability problems, and propose repairs. Yet no controlled benchmark measures…
The Anatomy of Scam Scenarios: Large-Scale Characterization and Conversation-Aware Detection
Shang Ma, Chen Yanai, Avichai Ben +3
Online scams have become a pervasive global threat, causing substantial financial, psychological, and operational harm. Scammers embed psychological techniques (PTs) within reusabl…
SpecAlign: Efficient Specification-Grounded Alignment of Large Language Models via Synthetic Data
Wenjie Wang, Yue Huang, Zhengqing Yuan +6
As large language models (LLMs) are increasingly deployed in real-world applications, alignment is no longer governed by a single universal notion of safety or helpfulness, but ins…
Comparing Human Oversight Strategies for Computer-Use Agents
Chaoran Chen, Zhiping Zhang, Zeya Chen +9
LLM-powered computer-use agents (CUAs) shift users from direct manipulation to supervising an unfolding action sequence, yet existing oversight research mostly evaluates static dec…
Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
Jingyu Tang, Chaoran Chen, Jiawen Li +11
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 ris…
My Favorite Streamer is an LLM: Discovering, Bonding, and Co-Creating in AI VTuber Fandom
Jiayi Ye, Chaoran Chen, Yue Huang +3
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 cultur…
The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections
Chaoran Chen, Zhiping Zhang, Bingcan Guo +8
A Large Language Model (LLM) powered GUI agent is a specialized autonomous system that performs tasks on the user's behalf according to high-level instructions. It does so by perce…
Toward a Human-Centered Evaluation Framework for Trustworthy LLM-Powered GUI Agents
Chaoran Chen, Zhiping Zhang, Ibrahim Khalilov +7
The rise of Large Language Models (LLMs) has revolutionized Graphical User Interface (GUI) automation through LLM-powered GUI agents, yet their ability to process sensitive data wi…
CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applications
Chaoran Chen, Daodao Zhou, Yanfang Ye +2
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), introd…
Careful About What App Promotion Ads Recommend! Detecting and Explaining Malware Promotion via App Promotion Graph
Shang Ma, Chaoran Chen, Shao Yang +5
In Android apps, their developers frequently place app promotion ads, namely advertisements to promote other apps. Unfortunately, the inadequate vetting of ad content allows malici…
Why am I seeing this: Democratizing End User Auditing for Online Content Recommendations
Chaoran Chen, Leyang Li, Luke Cao +4
Personalized recommendation systems tailor content based on user attributes, which are either provided or inferred from private data. Research suggests that users often hypothesize…
An Empathy-Based Sandbox Approach to Bridge the Privacy Gap among Attitudes, Goals, Knowledge, and Behaviors
Chaoran Chen, Weijun Li, Wenxin Song +3
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 syst…