GUI Agents: A Survey
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

TL;DR
This survey reviews the development, architectures, and evaluation of GUI agents powered by large foundation models, highlighting their capabilities, challenges, and future research directions in automating human-computer interaction.
Contribution
It provides a comprehensive categorization and unified framework for GUI agents, summarizing current progress, benchmarks, and open challenges in the field.
Findings
Categorization of benchmarks and evaluation metrics
Unified framework for perception, reasoning, and acting
Identification of open challenges and future directions
Abstract
Graphical User Interface (GUI) agents, powered by Large Foundation Models, have emerged as a transformative approach to automating human-computer interaction. These agents autonomously interact with digital systems or software applications via GUIs, emulating human actions such as clicking, typing, and navigating visual elements across diverse platforms. Motivated by the growing interest and fundamental importance of GUI agents, we provide a comprehensive survey that categorizes their benchmarks, evaluation metrics, architectures, and training methods. We propose a unified framework that delineates their perception, reasoning, planning, and acting capabilities. Furthermore, we identify important open challenges and discuss key future directions. Finally, this work serves as a basis for practitioners and researchers to gain an intuitive understanding of current progress, techniques,…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Web Data Mining and Analysis · Gaze Tracking and Assistive Technology
