GUI agent: Guided Exploration of User-Sensitive Screens

Source

• Source name: arXiv
• Source kind: paper
• Authors / organization: Aradhana Nayak, Mussadiq Nazeer, Wang Peng, Feng Liu
• Venue: arXiv: cs.AI
• Published: 2026-06-24
• Collected: 2026-06-25
• URL: http://arxiv.org/abs/2606.25705v1
• PDF: https://arxiv.org/pdf/2606.25705v1
• DOI: UNKNOWN

Plain-Language Brief

The text discusses a paper that proposes a solution for a problem in Large Language Model (LLM) agents used within Graphical User Interface (GUI) environments. The current issue is that these agents, fine-tuned to complete tasks regardless of safety implications, often encounter user-sensitive information and may require human takeover. This paper presents an explorer agent designed to identify queries leading to user-sensitive states in a GUI environment.

What the Document Says

• The text discusses the use of LLM agents in open GUI environments.
• It mentions that these agents often encounter user-sensitive information.
• The authors state that current LLM-driven agents are fine-tuned to complete tasks regardless of safety implications, making real-world deployment difficult and affecting reliability.
• They propose the need for identifying and categorizing user-sensitive states and defining user-sensitive queries.
• The paper develops an explorer agent that systematically explores the query space starting from one demonstrated task to identify queries leading to user-sensitive states.

Key Concepts Mentioned

• Large Language Model (LLM) agents
• Graphical User Interface (GUI)
• user-sensitive information
• query space
• explorer agent

Claims Made by the Document

• Current LLM-driven agents are difficult to deploy in real-world scenarios due to their actions ignoring safety implications.
• Identifying and categorizing user-sensitive states and queries is crucial for handing over control to users in critical scenarios.

Evidence Used

• The text mentions that current LLM-driven agents are fine-tuned to complete tasks regardless of safety implications.
• The authors propose an explorer agent to identify queries leading to user-sensitive states.

Methods / Approach

UNKNOWN

Limitations Stated by the Authors

UNKNOWN

Limitations Noted by the Agent

Agent interpretation — not from the source.

UNKNOWN

Open Questions

UNKNOWN

Notes for Future Q&A

May include interpretation. Labeled where it does.

UNKNOWN

Raw Abstract / Excerpt

LLM agents are increasingly being used to automate tasks for users within an open GUI environment. They inevitably encounter screens containing user-sensitive information, for which takeover of task execution by the user is highly desirable or even necessary. State-of-the-art LLM-driven agents are usually fine-tuned to complete tasks regardless of the safety implications of their actions. This makes their real-world deployment difficult and adversely affects the reliability. Therefore, it is crucial to identify and categorize user-sensitive states and define user-sensitive queries. This dataset would be to engineers to recognize and request handover to the user in critical scenarios. This short paper develops an explorer agent that systematically explores the query space starting from one demonstrated task to identify queries that, if executed, would lead to user-sensitive states in a GUI environment.