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WorldGUI: An Interactive Benchmark for Desktop GUI Automation from Any Starting Point
Henry Hengyu · 2026-05-26 · via cs.AI updates on arXiv.org

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Abstract:Recent progress in GUI agents has substantially improved visual grounding, yet robust planning remains challenging, particularly when the environment deviates from a canonical initial state. In real applications, users often invoke assistance mid-workflow, where software may be partially configured, steps may have been executed in different orders, or the interface may differ from its default setup. Such task-state variability is pervasive but insufficiently evaluated in existing GUI benchmarks. To address this gap, we introduce WorldGUI, a benchmark covering ten widely used desktop and web applications with tasks instantiated under diverse, systematically constructed initial states. These variations capture realistic human-computer interaction settings and enable diagnostic evaluation of an agent's ability to recover, adapt plans, and handle non-default contexts. We further present WorldGUI-Agent, a simple and model-agnostic framework that organizes planning and execution around three critique stages, improving reliability in dynamic environments. Experiments demonstrate that state-of-the-art GUI agents exhibit substantial performance degradation under non-default initial conditions, revealing limited robustness and fragile planning behaviors. Our benchmark and framework provide a foundation for developing more adaptable and reliable GUI agents. The code and data are available at this https URL.
Comments: Technique Report
Subjects: Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)
Cite as: arXiv:2502.08047 [cs.AI]
  (or arXiv:2502.08047v5 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2502.08047

arXiv-issued DOI via DataCite

Submission history

From: Zhao Hengyuan [view email]
[v1] Wed, 12 Feb 2025 01:06:10 UTC (7,833 KB)
[v2] Wed, 19 Feb 2025 23:27:05 UTC (7,811 KB)
[v3] Mon, 9 Jun 2025 06:58:38 UTC (8,891 KB)
[v4] Sun, 22 Feb 2026 18:05:26 UTC (19,005 KB)
[v5] Sat, 23 May 2026 20:19:43 UTC (8,826 KB)