English

GUI Agents: A Survey

Artificial Intelligence 2025-09-30 v3 Human-Computer Interaction

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, benchmarks, and critical open problems that remain to be addressed.

Keywords

Cite

@article{arxiv.2412.13501,
  title  = {GUI Agents: A Survey},
  author = {Dang Nguyen and Jian Chen and Yu Wang and Gang Wu and Namyong Park and Zhengmian Hu and Hanjia Lyu and Junda Wu and Ryan Aponte and Yu Xia and Xintong Li and Jing Shi and Hongjie Chen and Viet Dac Lai and Zhouhang Xie and Sungchul Kim and Ruiyi Zhang and Tong Yu and Mehrab Tanjim and Nesreen K. Ahmed and Puneet Mathur and Seunghyun Yoon and Lina Yao and Branislav Kveton and Jihyung Kil and Thien Huu Nguyen and Trung Bui and Tianyi Zhou and Ryan A. Rossi and Franck Dernoncourt},
  journal= {arXiv preprint arXiv:2412.13501},
  year   = {2025}
}

Comments

Accepted to Findings of ACL 2025

R2 v1 2026-06-28T20:39:52.130Z