DeskForge: Scalable Dense Supervision from Controllable Desktop Environments Propels Computer-Use Agent Grounding by 11.5%
Computer-use agents face fundamental grounding bottlenecks in real-world desktop environments due to layered windows, shifting layouts, and visually indistinguishable controls. Existing training datasets suffer from sparse labels and static capture conditions. Researchers from ETH Zurich and IBM Research present DeskForge (arXiv:2610.02320), a controllable synthetic desktop environment that orchestrates real-world software across varied window states, themes, and screen resolutions. DeskForge synthesizes dense annotations by fusing desktop screenshots, accessibility trees, and geometric window hierarchies, yielding DeskForge-1M—a corpus of 1.2M observations and 159.7M annotated UI element instances. Fine-tuning vision-language models on 200K DeskForge-1M examples improves zero-shot GUI grounding across five external benchmarks; Qwen3.5-4B gains 11.51 percentage points on ScreenSpot-Pro and 10.11 points on OSWorld-G. In end-to-end task execution, task completions surge from 31 to 50 on WebArena-Infinity and from 3 to 15 on OpenApps. The dataset, models, and code are open-sourced at saidgurbuz.github.io/deskforge.
Key Takeaways
- ETH Zurich and IBM introduce DeskForge, a controllable environment synthesizing DeskForge-1M with 1.2M observations and 159.7M UI elements
- Fine-tuning Qwen3.5-4B boosts GUI grounding by 11.51 points on ScreenSpot-Pro and 10.11 points on OSWorld-G across five external benchmarks
- Multiplies long-horizon task completion: solves 50/119 tasks on WebArena-Infinity (up from 31) and 5x on OpenApps (from 3 to 15), fully open-sourced