Summary of Omniparser For Pure Vision Based Gui Agent, by Yadong Lu et al.
OmniParser for Pure Vision Based GUI Agent
by Yadong Lu, Jianwei Yang, Yelong Shen, Ahmed Awadallah
First submitted to arxiv on: 1 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel method called OmniParser to enhance the ability of large vision language models like GPT-4V to generate actions grounded in user interface screenshots. This is achieved by developing a comprehensive screen parsing technique that can reliably identify interactable icons and understand the semantics of various elements in a screenshot. The proposed approach involves fine-tuning specialized models for icon detection and caption generation, which are then utilized to improve the performance of GPT-4V on various benchmarks such as ScreenSpot, Mind2Web, and AITW. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces OmniParser, a method that helps large language models like GPT-4V understand user interface screenshots better. This is useful for generating actions that can be grounded in the correct regions of the screen. The approach involves detecting interactable icons and understanding the meaning of different elements on the screen. This makes it possible to improve the performance of GPT-4V on various tasks. |
Keywords
» Artificial intelligence » Fine tuning » Gpt » Parsing » Semantics
