Summary of Gui Agents: a Survey, by Dang Nguyen et al.

GUI Agents: A Survey

by Dang Nguyen, Jian Chen, Yu Wang, Gang Wu, Namyong Park, Zhengmian Hu, Hanjia Lyu, Junda Wu, Ryan Aponte, Yu Xia, Xintong Li, Jing Shi, Hongjie Chen, Viet Dac Lai, Zhouhang Xie, Sungchul Kim, Ruiyi Zhang, Tong Yu, Mehrab Tanjim, Nesreen K. Ahmed, Puneet Mathur, Seunghyun Yoon, Lina Yao, Branislav Kveton, Thien Huu Nguyen, Trung Bui, Tianyi Zhou, Ryan A. Rossi, Franck Dernoncourt

First submitted to arxiv on: 18 Dec 2024

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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 presents a comprehensive survey on Graphical User Interface (GUI) agents powered by Large Foundation Models, which have revolutionized the automation of human-computer interaction. GUI agents can autonomously interact with digital systems or software applications via GUIs, mimicking human actions like clicking, typing, and navigating visual elements across various platforms. The survey categorizes their benchmarks, evaluation metrics, architectures, and training methods, proposing a unified framework that outlines their perception, reasoning, planning, and acting capabilities. The paper identifies key challenges and future directions, serving as a foundation for practitioners and researchers to understand the current state of the field, its techniques, benchmarks, and open problems.
Low	GrooveSquid.com (original content)	Low Difficulty Summary GUI agents are smart tools that can talk to computers like humans do. They use large models to learn how to interact with different digital systems and software programs. This paper is like a guidebook that shows what these agents can do and how they work. It also talks about the challenges and next steps for making them better.