Beyond Clicking:A Step Towards Generalist GUI Grounding via Text Dragging

Fuente: arXiv
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Main Authors: Liao, Zeyi, Lu, Yadong, Gou, Boyu, Sun, Huan, Awadallah, Ahmed
Format: Preprint
Published: 2025
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author Liao, Zeyi
Lu, Yadong
Gou, Boyu
Sun, Huan
Awadallah, Ahmed
author_facet Liao, Zeyi
Lu, Yadong
Gou, Boyu
Sun, Huan
Awadallah, Ahmed
contents Graphical user interface (GUI) grounding, the process of mapping human instructions to GUI actions, serves as a fundamental basis to autonomous GUI agents. While existing grounding models achieve promising performance to simulate the mouse click action on various click-based benchmarks, another essential mode of mouse interaction, namely dragging, remains largely underexplored. Yet, dragging the mouse to select and manipulate textual content represents a prevalent and important usage in practical GUI scenarios. To narrow this gap, we first introduce GUI-Drag, a diverse dataset of 161K text dragging examples synthesized through a scalable pipeline. To support systematic and robust evaluation, we further construct ScreenDrag, a benchmark with 5,333 examples spanning three levels of interface context, together with three dedicated metrics designed for assessing text dragging capability. Models trained on GUI-Drag with an efficient continual training strategy achieve substantial improvements on ScreenDrag, while preserving the original click-based performance on ScreenSpot, ScreenSpot-v2, and OSWorld-G. Our work encourages further research on broader GUI grounding beyond just clicking and paves way toward a truly generalist GUI grounding model. All benchmark, data, checkpoints, and code are open-sourced and available at https://osu-nlp-group.github.io/GUI-Drag.
format Preprint
id arxiv_https___arxiv_org_abs_2601_06031
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Beyond Clicking:A Step Towards Generalist GUI Grounding via Text Dragging
Liao, Zeyi
Lu, Yadong
Gou, Boyu
Sun, Huan
Awadallah, Ahmed
Human-Computer Interaction
Artificial Intelligence
Graphical user interface (GUI) grounding, the process of mapping human instructions to GUI actions, serves as a fundamental basis to autonomous GUI agents. While existing grounding models achieve promising performance to simulate the mouse click action on various click-based benchmarks, another essential mode of mouse interaction, namely dragging, remains largely underexplored. Yet, dragging the mouse to select and manipulate textual content represents a prevalent and important usage in practical GUI scenarios. To narrow this gap, we first introduce GUI-Drag, a diverse dataset of 161K text dragging examples synthesized through a scalable pipeline. To support systematic and robust evaluation, we further construct ScreenDrag, a benchmark with 5,333 examples spanning three levels of interface context, together with three dedicated metrics designed for assessing text dragging capability. Models trained on GUI-Drag with an efficient continual training strategy achieve substantial improvements on ScreenDrag, while preserving the original click-based performance on ScreenSpot, ScreenSpot-v2, and OSWorld-G. Our work encourages further research on broader GUI grounding beyond just clicking and paves way toward a truly generalist GUI grounding model. All benchmark, data, checkpoints, and code are open-sourced and available at https://osu-nlp-group.github.io/GUI-Drag.
title Beyond Clicking:A Step Towards Generalist GUI Grounding via Text Dragging
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2601.06031