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arXiv · 2411.13591

Improved GUI Grounding via Iterative Narrowing

Anthony Nguyen
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Abstract

Graphical User Interface (GUI) grounding plays a crucial role in enhancing the capabilities of Vision-Language Model (VLM) agents. While general VLMs, such as GPT-4V, demonstrate strong performance across various tasks, their proficiency in GUI grounding remains suboptimal. Recent studies have focused on fine-tuning these models specifically for zero-shot GUI grounding, yielding significant improvements over baseline performance. We introduce a visual prompting framework that employs an iterative narrowing mechanism to further improve the performance of both general and fine-tuned models in GUI grounding. For evaluation, we tested our method on a comprehensive benchmark comprising various UI platforms and provided the code to reproduce our results.

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Anthony Nguyen. 2024-11-18. Improved GUI Grounding via Iterative Narrowing. https://arxiv.org/abs/2411.13591

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