--- license: cc-by-4.0 language: - zh tags: - agent pretty_name: CMGUI size_categories: - 100KCMGUI Dataset

๐Ÿ“„ Project | ๐ŸŒ Model in Hugging Face | ๐ŸŒ Model in ModelScope

English | ็ฎ€ไฝ“ไธญๆ–‡

**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 Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.