87 citations · 111 across the 10 of their papers we have counts for
9 papers · 1 filter
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…
Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents
Zhiping Zhang, Yi Evie Zhang, Freda Shi +1
LLM agents require personal information for personalization in order to effectively act on users' behalf, but this raises privacy concerns that can discourage data sharing, limitin…
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…
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…
Privacy Leakage Overshadowed by Views of AI: A Study on Human Oversight of Privacy in Language Model Agent
Zhiping Zhang, Bingcan Guo, Tianshi Li
Language model (LM) agents that act on users' behalf for personal tasks (e.g., replying emails) can boost productivity, but are also susceptible to unintended privacy leakage risks…
Secret Use of Large Language Model (LLM)
Zhiping Zhang, Chenxinran Shen, Bingsheng Yao +2
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 d…
Human-Centered Privacy Research in the Age of Large Language Models
Tianshi Li, Sauvik Das, Hao-Ping Lee +3
The emergence of large language models (LLMs), and their increased use in user-facing systems, has led to substantial privacy concerns. To date, research on these privacy concerns…
"It's a Fair Game", or Is It? Examining How Users Navigate Disclosure Risks and Benefits When Using LLM-Based Conversational Agents
Zhiping Zhang, Michelle Jia, Hao-Ping Lee +5
The widespread use of Large Language Model (LLM)-based conversational agents (CAs), especially in high-stakes domains, raises many privacy concerns. Building ethical LLM-based CAs…