arXiv:2511.07332v2 Announce Type: replace Abstract: Building reliable computer-use agents requires grounding: accurately connecting natural language instructions to the correct on-screen elements. While large datasets exist for web and mobile interactions, high-quality resources for desktop environments are limited. To address this gap, we introduce GroundCUA, a large-scale desktop grounding dataset built from expert human demonstrations. It covers 87 applications across 12 categories and includes 56K screenshots, with every on-screen element carefully annotated for a total of over 3.56M human
The development of robust AI agents for desktop environments is a critical next step as general AI capabilities advance, making such datasets essential to bridge the gap between AI research and practical application.
This development addresses a key bottleneck in AI agent development, promising to unlock new levels of automation for knowledge work and human-computer interaction across various industries.
The availability of large, high-quality datasets for desktop grounding will significantly accelerate the training and deployment of AI agents capable of operating complex software applications autonomously.
- · AI software developers
- · Enterprise software users
- · Automation platforms
- · Productivity software companies
- · Tasks requiring manual repetitive desktop operations
- · Legacy automation providers
Desktop AI agents will become more sophisticated and capable of handling a wider range of tasks previously requiring human intervention.
Increased reliance on AI agents will lead to the automation of many white-collar workflows, changing job roles and increasing demand for agent oversight.
The proliferation of highly capable desktop agents could enable new forms of enterprise intelligence and workflow optimization, fundamentally altering the competitive landscape for businesses that adopt them efficiently.
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Read at arXiv cs.LG