most citedToward a Human-Centered Evaluation Framework for Trustworthy LLM-Powered GUI Agents

1 citations · 2 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

Using Grounded Theory for Agent Behavior Analysis at Scale

Zhuoran Lu, Yangyang Yu, Zhuoyan Li +5

Understanding agent behavior requires methods that scale to thousands of trajectories and surface new patterns in long, often unfamiliar tasks where pre-built classifiers fall shor…

cs.AI2026

How to Interpret Agent Behavior

Jie Gao, Kaiser Sun, Jen-tse Huang +8

Autonomous agents such as Claude Code and Codex now operate for hours or even days. Understanding their runtime behavior has become critical for downstream tasks such as diagnosing…

cs.HC2026

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…

cs.HC2026

Disclose with Care: Designing Privacy Controls in Interview Chatbots

Ziwen Li, Ziang Xiao, Tianshi Li

Collecting data on sensitive topics remains challenging in HCI, as participants often withhold information due to privacy concerns and social desirability bias. While chatbots' per…

cs.SE2026

PriviSense: A Frida-Based Framework for Multi-Sensor Spoofing on Android

Ibrahim Khalilov, Chaoran Chen, Ziang Xiao +3

Mobile apps increasingly rely on real-time sensor and system data to adapt their behavior to user context. While emulators and instrumented builds offer partial solutions, they oft…

cs.HC2025★ 1 cited

Beyond Permissions: Investigating Mobile Personalization with Simulated Personas

Ibrahim Khalilov, Chaoran Chen, Ziang Xiao +3

Mobile applications increasingly rely on sensor data to infer user context and deliver personalized experiences. Yet the mechanisms behind this personalization remain opaque to use…

cs.HC2025

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…

cs.HC2025

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…

cs.HC2025★ 1 cited

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…