AIHCDec 18, 2024

GUI Agents: A Survey

arXiv:2412.13501v399 citationsh-index: 41ACL
Originality Synthesis-oriented
AI Analysis

It serves as a basis for practitioners and researchers to understand current progress and open challenges in automating human-computer interaction.

The paper provides a comprehensive survey of GUI agents, categorizing benchmarks, evaluation metrics, architectures, and training methods, and proposes a unified framework for their capabilities.

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.

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