arXiv:2606.31410v1 Announce Type: new Abstract: Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real applications through interface actions such as tapping, swiping, text entry, and navigation. However, existing GUI agents are trained and evaluated largely on offline trajectories, simulated environments, and standardized benchmarks. These differ substantially from real applications in interface layout, interaction logic, and abnormal-state distribution, and cannot faithfully characterize execution stability in real-world use, where acc
The rapid advancement in vision-language models makes end-to-end GUI agents feasible, leading to focused development on practical applications beyond simulated environments.
This development represents a critical step towards more robust and universally applicable AI agents for interacting with digital interfaces, enhancing productivity and automation.
The focus is shifting from theoretical or simulated GUI agent performance to real-world execution stability and reliability across diverse applications.
- · AI Agent Developers
- · Smartphone Manufacturers
- · Productivity Software
- · Digital Service Providers
- · Tasks Requiring Manual Interface Interaction
- · Outdated Automation Solutions
More sophisticated and reliable AI agents capable of performing complex tasks on any digital interface.
Increased demand for robust, adaptable UI/UX design that is agent-friendly, and a potential for new interface paradigms.
Accelerated automation across white-collar tasks, potentially leading to significant workforce restructuring and new economic models.
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Read at arXiv cs.AI