Datasets:
sunorme
/

Languages:
Chinese
ArXiv:
Tags:
agent
License:
CMGUI / README.md
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Duplicate from alibabagroup/CMGUI
6310b8f
---
license: cc-by-4.0
language:
- zh
tags:
- agent
pretty_name: CMGUI
size_categories:
- 100K<n<1M
---
# <p align="center"><b>CMGUI Dataset</b></p>
<p align="center">
๐Ÿ“„ <a href="https://github.com/alibaba/MobiZen-GUI"> Project </a> |
๐ŸŒ <a href="https://huggingface.co/alibabagroup/MobiZen-GUI-4B">Model in Hugging Face</a> |
๐ŸŒ <a href="https://modelscope.cn/models/GUIAgent/MobiZen-GUI-4B">Model in ModelScope</a>
<p align="center">
<a href="https://huggingface.co/datasets/alibabagroup/CMGUI/blob/main/README.md">English</a> |
<a href="https://huggingface.co/datasets/alibabagroup/CMGUI/blob/main/README_CN.md">็ฎ€ไฝ“ไธญๆ–‡</a>
</p>
**CMGUI** (Chinese Mobile GUI) is a large-scale, high-quality dataset constructed for developing GUI agents on Chinese mobile applications. The dataset contains **18k episodes** (i.e., trajectories) with **98k steps** collected from more than **50** real-world Chinese mobile apps, covering diverse functional domains such as e-commerce (e.g., Taobao, Pinduoduo), social media (e.g., Rednote, Douyin), and local services (e.g., Meituan, Amap).
**CMGUI-Bench**, the corresponding navigation benchmark derived from CMGUI, comprises 386 episodes and 2,547 steps spanning 44 widely used Chinese apps, featuring multi-choice action annotations to accommodate diverse GUI manipulations where multiple valid actions may exist in each step. Both CMGUI and CMGUI-Bench are rigorously human-verified with precise bounding box annotations, addressing the critical scarcity of high-quality open-source Chinese mobile GUI datasets.
### Key Features
- **Chinese-focused**: Specifically designed for Chinese mobile applications and mobile user interactions
- **High-quality annotations**: Each episode includes human-verified actions and human-annotated bounding boxes
- **Multi-resolution support**: Screenshots captured at various device resolutions (e.g., 720x1280, 1080x2400, 1440x3200)
- **Rich action space**: Supports CLICK, TYPE, SWIPE, and other common mobile interaction patterns
- **Real-world tasks**: Instructions are designed to reflect practical user scenarios in Chinese mobile app ecosystems
## Dataset Structure
The CMGUI dataset is organized as follows:
```
CMGUI/
โ”œโ”€โ”€ README.md # This file
โ”œโ”€โ”€ episode_annotation_train.jsonl # Training episode annotations (JSONL format, one episode per line)
โ”œโ”€โ”€ episode_annotation_test.jsonl # Testing/benchmarking episode annotations (JSONL format, one episode per line)
โ”œโ”€โ”€ screenshot_zip/ # Directory containing screenshot archives
โ”‚ โ”œโ”€โ”€ screenshot_train.zip # Main screenshot archive for training
โ”‚ โ”œโ”€โ”€ screenshot_train.z01 # Split archive part 1
โ”‚ โ”œโ”€โ”€ screenshot_train.z02 # Split archive part 2
โ”‚ โ”œโ”€โ”€ ...
โ”‚ โ””โ”€โ”€ screenshot_test.zip # Screenshot archive for testing/benchmarking
โ””โ”€โ”€ screenshot/ # Extracted screenshots (PNG files)
โ”œโ”€โ”€ 47b85366-5449-4894-9ece-beb2b1b41ced.png
โ”œโ”€โ”€ 4c0cd4d6-4935-42b2-a867-cf4f4142d2f0.png
โ””โ”€โ”€ ...
```
## Episode Annotation Format
The dataset is split into training and testing sets, stored in `episode_annotation_train.jsonl` and `episode_annotation_test.jsonl` respectively. Each line in these JSONL files represents one episode. Below is the detailed field description:
### Episode Data Fields
| Field | Type | Description |
|-------|------|-------------|
| `split` | `str` | Dataset split identifier ("train" or "test") |
| `episode_id` | `int` | Unique identifier for this episode |
| `instruction` | `str` | Natural language instruction describing the task (in Chinese) |
| `app` | `str` | Name of the primary mobile application used in this episode |
| `episode_length` | `int` | Total number of steps in this episode |
### Step Data Fields
The `step_data` field is a list of step objects, each containing the following fields:
| Field | Type | Description |
|-------|------|-------------|
| `step_id` | `int` | Zero-indexed step number indicating the position in the episode sequence |
| `screenshot` | `str` | Filename of the screenshot for this step (located in `screenshot/` directory) |
| `screenshot_width` | `int` | Width of the screenshot in pixels |
| `screenshot_height` | `int` | Height of the screenshot in pixels |
| `action` | `str` | The action type performed at this step. See below for action types |
| `type_text` | `str` | Text input for TYPE actions; empty string for other action types |
| `touch_coord` | `list[int]` | Touch coordinates `[x, y]` where the action starts. `[-1, -1]` for non-coordinate actions |
| `lift_coord` | `list[int]` | Lift coordinates `[x, y]` where the action ends. `[-1, -1]` for non-coordinate actions |
| `bbox` | `list[list[int]]` | List of bounding box coordinates `[[x1, y1, x2, y2], ...]` of the target UI element(s). Empty list `[]` if not applicable |
**Note:** In the train split, the number of bounding boxes in `bbox` is less than or equal to 1; in the test split, the number of bounding boxes in `bbox` can greater than 1, indicating that multiple UI elements are valid to click on in the corresponding step.
### Action Types
| Action | Description | Parameter |
|--------|-------------|------------------|
| **CLICK** | Single tap/click on a UI element | `touch_coord` = `lift_coord` = click position |
| **LONG_PRESS** | Long press on a UI element | `touch_coord` = `lift_coord` = press position |
| **SWIPE** | Swipe/scroll gesture | `touch_coord` = start position, `lift_coord` = end position |
| **TYPE** | Text input action | text in `type_text` |
| **KEY_BACK** | Press Back button | - |
| **KEY_HOME** | Press Home button | - |
| **WAIT** | Wait for page/content to load | - |
| **STOP** | Task completion signal | - |
### Coordinate System
- All coordinates are in **absolute pixel values** relative to the screenshot dimensions
- Origin `(0, 0)` is at the **top-left corner** of the screen
- Bounding box format: `[[x1, y1, x2, y2], ...]` where each `(x1, y1)` is the top-left corner and `(x2, y2)` is the bottom-right corner of a UI element
### Example Episode Structure
```json
{
"split": "train",
"episode_id": 0,
"instruction": "ๆ‰“ๅผ€่…พ่ฎฏๅœฐๅ›พ๏ผŒๆœ็ดขโ€œๆœ›ไบฌๅŒป้™ขโ€๏ผŒๅ‘่ตทๆญฅ่กŒๅฏผ่ˆช",
"app": "่…พ่ฎฏๅœฐๅ›พ",
"episode_length": 9,
"step_data": [
{
"step_id": 0,
"screenshot": "47b85366-5449-4894-9ece-beb2b1b41ced.png",
"screenshot_width": 1080,
"screenshot_height": 2400,
"action": "CLICK",
"type_text": "",
"touch_coord": [
538,
643
],
"lift_coord": [
538,
643
],
"bbox": [
[
474,
581,
604,
708
]
]
},
// ... more steps
]
}
```
## Screenshots Extraction Instructions
To extract all screenshots to the `screenshot/` directory:
**Training screenshots:**
```bash
unzip screenshot_zip/screenshot_train.zip -d .
```
The `unzip` command will automatically detect and merge the split archives (`.z01`, `.z02`, etc.) during extraction.
**Test screenshots:**
```bash
unzip screenshot_zip/screenshot_test.zip -d .
```
## Citation
If you find this dataset helpful in your research, please cite the following paper:
```
@article{xie2026secagent,
title={SecAgent: Efficient Mobile GUI Agent with Semantic Context},
author={Yiping Xie and Song Chen and Jingxuan Xing and Wei Jiang and Zekun Zhu and Yingyao Wang and Pi Bu and Jun Song and Yuning Jiang and Bo Zheng},
journal={arXiv preprint arXiv:2603.08533},
year={2026}
}
```
## License
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.