DragOn: A Benchmark and Dataset for Drag-Based GUI Interactions
GUI agents - vision-based models that control desktops, web browsers, and mobile devices through graphical user interfaces - promise to automate a wide range of digital tasks. While million-scale datasets have enabled substantial progress on click-grounding, drag grounding (e.g. drag-and-drop, swipe, highlight) data remains an order of magnitude smaller and current models fall short on complex drag-based interactions. We introduce DragOn, a drag grounding benchmark and training dataset covering four domains: text highlighting, cell selection, element resizing and slider manipulation. The dataset comprises 286K training screenshots and 3.5M training tasks, plus a 2000-example held-out eval...
| Authors | Nathan Bout, Maxime Langevin, Ronan Riochet |
|---|---|
| Primary category | cs.AI |
| Published | 4 June 2026 |
| Last updated at source | 4 June 2026 |
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