LLM-Powered GUI Agents in Phone Automation: Surveying Progress and Prospects
December 2, 2025 · View on GitHub
🚀 News
- 🏆 [2025/12/02] Our survey has been accepted to TMLR 2025! See the latest version: LLM-Powered GUI Agents in Phone Automation: Surveying Progress and Prospects.
- 🥳 [2025/04/29] Our survey has been updated for v2! See LLM-Powered GUI Agents in Phone Automation: Surveying Progress and Prospects for the paper! Welcome to follow our work.
- 🤩 [2025/03/13] We have updated the Paper List again! We will update once a week from now on. We welcome your continued interest in our work!
- 🎉 [2025/02/21] We have updated the Paper List! The new version of our survey will be released later.
- 💥 [2025/01/07] Our survey is released!
- ✨ [2024/12/29] We create this repository to maintain a paper list on LLM-Powered Phone GUI Agents. More papers are coming soon!
📑 Citation
If you find our survey useful for your research and applications, please cite using this BibTeX:
@article{liu2025llm,
title={Llm-powered gui agents in phone automation: Surveying progress and prospects},
author={Liu, Guangyi and Zhao, Pengxiang and Liu, Liang and Guo, Yaxuan and Xiao, Han and Lin, Weifeng and Chai, Yuxiang and Han, Yue and Ren, Shuai and Wang, Hao and others},
journal={arXiv preprint arXiv:2504.19838},
year={2025}
}
📖 Introduction
🔥 Must-read papers for LLM-Powered Phone GUI Agents.
We greatly appreciate any contributions via PRs, issues, emails, or other methods.
🔖 General Overview
A comprehensive taxonomy of LLM-powered phone GUI agents in phone automation. Note that only a selection of representative works is included in this categorization.
🪧 Milestones
Milestones in the development of LLM-powered phone GUI agents. This figure divides advancements into four primary parts: Prompt Engineering, Training-Based Methods, Datasets and Benchmarks. Prompt Engineering leverages pre-trained LLMs by strategically crafting input prompts, to perform specific tasks without modifying model parameters. In contrast, Training-Based Methods, involve adapting LLMs via supervised fine-tuning or reinforcement learning on GUI-specific data, thereby enhancing their ability to understand and interact with mobile UIs.
📝 Table of Content (ToC)
- LLM-Powered GUI Agents in Phone Automation: Surveying Progress and Prospects