AndroidDaily Dataset

This repository hosts the AndroidDaily dataset, a benchmark grounded in real-world mobile usage patterns, introduced in the paper Step-GUI Technical Report.

The AndroidDaily benchmark comprises 3146 static actions and 235 end-to-end tasks across high-frequency daily scenarios. It is specifically designed to assess whether GUI agents can handle authentic everyday usage, providing a robust evaluation for GUI automation capabilities.

• Project Page: https://opengelab.github.io/
• Code: https://github.com/stepfun-ai/gelab-zero

Sample Usage

The AndroidDaily dataset is primarily used for training and evaluating GUI agents, particularly the GELab-Zero agent. The following steps, adapted from the GELab-Zero GitHub repository, demonstrate how to set up the environment and run a single task.

1. LLM Inference Environment Setup (Ollama)

First, install Ollama (refer to https://ollama.com/ for full instructions). Then, download and import the gelab-zero-4b-preview model:

# If huggingface cli is not installed yet, execute this command first
pip install huggingface_hub

# Download the gelab-zero-4b-preview model weights from huggingface
hf download --no-force-download stepfun-ai/GELab-Zero-4B-preview --local-dir gelab-zero-4b-preview

# Import the model into ollama
cd gelab-zero-4b-preview
ollama create gelab-zero-4b-preview -f Modelfile

2. Android Device Execution Environment Setup

Ensure your Android device has Developer Mode and USB Debugging enabled. Install ADB tools and connect your device. You can verify the connection:

adb devices

Expected output:

List of devices attached
AN2CVB4C28000731        device

3. GELab-Zero Agent Runtime Environment Setup and Run a Task

Clone the GELab-Zero repository, install dependencies, and run a single task:

# Clone the repository
git clone https://github.com/stepfun-ai/gelab-zero
cd gelab-zero

# Install dependencies
pip install -r requirements.txt

# To inference a single task
python examples/run_single_task.py

This will execute an example task, saving trajectories to the running_log/server_log/os-copilot-local-eval-logs/ directory.

Citation

If you find the AndroidDaily dataset or GELab-Zero useful for your research, please consider citing our work:

@misc{yan2025stepguitechnicalreport,
      title={Step-GUI Technical Report}, 
      author={Haolong Yan and Jia Wang and Xin Huang and Yeqing Shen and Ziyang Meng and Zhimin Fan and Kaijun Tan and Jin Gao and Lieyu Shi and Mi Yang and Shiliang Yang and Zhirui Wang and Brian Li and Kang An and Chenyang Li and Lei Lei and Mengmeng Duan and Danxun Liang and Guodong Liu and Hang Cheng and Hao Wu and Jie Dong and Junhao Huang and Mei Chen and Renjie Yu and Shunshan Li and Xu Zhou and Yiting Dai and Yineng Deng and Yingdan Liang and Zelin Chen and Wen Sun and Chengxu Yan and Chunqin Xu and Dong Li and Fengqiong Xiao and Guanghao Fan and Guopeng Li and Guozhen Peng and Hongbing Li and Hang Li and Hongming Chen and Jingjing Xie and Jianyong Li and Jingyang Zhang and Jiaju Ren and Jiayu Yuan and Jianpeng Yin and Kai Cao and Liang Zhao and Liguo Tan and Liying Shi and Mengqiang Ren and Min Xu and Manjiao Liu and Mao Luo and Mingxin Wan and Na Wang and Nan Wu and Ning Wang and Peiyao Ma and Qingzhou Zhang and Qiao Wang and Qinlin Zeng and Qiong Gao and Qiongyao Li and Shangwu Zhong and Shuli Gao and Shaofan Liu and Shisi Gao and Shuang Luo and Xingbin Liu and Xiaojia Liu and Xiaojie Hou and Xin Liu and Xuanti Feng and Xuedan Cai and Xuan Wen and Xianwei Zhu and Xin Liang and Xin Liu and Xin Zhou and Yingxiu Zhao and Yukang Shi and Yunfang Xu and Yuqing Zeng and Yixun Zhang and Zejia Weng and Zhonghao Yan and Zhiguo Huang and Zhuoyu Wang and Zheng Ge and Jing Li and Yibo Zhu and Binxing Jiao and Xiangyu Zhang and Daxin Jiang},
      year={2025},
      eprint={2512.15431},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2512.15431}, 
}

@software{gelab_zero_2025,
  title={GELab-Zero: An Advanced Mobile Agent Inference System},
  author={GELab Team},
  year={2025},
  url={https://github.com/stepfun-ai/gelab-zero}
}

@misc{gelab_engine,
      title={GUI Exploration Lab: Enhancing Screen Navigation in Agents via Multi-Turn Reinforcement Learning}, 
      author={Haolong Yan and Yeqing Shen and Xin Huang and Jia Wang and Kaijun Tan and Zhixuan Liang and Hongxin Li and Zheng Ge and Osamu Yoshie and Si Li and Xiangyu Zhang and Daxin Jiang},
      year={2025},
      eprint={2512.02423},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2512.02423}, 
}