arXiv:2606.04701v1 Announce Type: cross Abstract: GUI agents today assume a static screen, where the world is frozen between two actions. However, real interfaces such as short-video applications violate this assumption, as their content keeps playing, and a competent user must decide what to watch and for how long. We formalize this task as Living-Screen-Native GUI agents and introduce LivingScreen, the first benchmark instantiating it on short-video platforms, with a faithful browser-based environment, a three-tier task suite, and metrics that jointly score accuracy and information efficienc
The proliferation of dynamic, interactive digital interfaces, particularly short-video platforms, necessitates a re-evaluation of GUI agent capabilities beyond static screen assumptions.
This development addresses a critical limitation in current AI agent design, pushing towards more human-like interaction with complex, real-time digital environments, impacting automation potential.
The introduction of 'Living-Screen-Native' GUI agents acknowledges and quantifies the challenge of dynamic interfaces, leading to more robust and versatile AI automation.
- · AI agent developers
- · Short-video platforms (for user engagement insights)
- · Automation software providers
- · Legacy GUI automation tools
- · Companies relying on simplistic RPA solutions
The benchmark provides a standardized method to evaluate AI agents' performance on dynamic interfaces.
Improved AI agents could lead to advanced automated content consumption and interaction strategies on platforms, potentially influencing information dissemination.
The concept of 'living-screen' interaction could extend beyond GUI agents to other autonomous systems interacting with real-time, dynamic information displays.
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Read at arXiv cs.CL