README_zh.md · 个人收藏室/MobileAgent

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<h3>Mobile-Agent: 强大的移动设备操作助手家族<h3>
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	<a href="https://huggingface.co/spaces/junyangwang0410/Mobile-Agent"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm-dark.svg" alt="Open in Spaces"></a>
	<a href="https://modelscope.cn/studios/wangjunyang/Mobile-Agent-v2"><img src="assets/Demo-ModelScope-brightgreen.svg" alt="Demo ModelScope"></a>
  <a href="https://arxiv.org/abs/2401.16158"><img src="https://img.shields.io/badge/Arxiv-2401.16158-b31b1b.svg?logo=arXiv" alt=""></a>
  <a href="https://arxiv.org/abs/2406.01014 "><img src="https://img.shields.io/badge/Arxiv-2406.01014-b31b1b.svg?logo=arXiv" alt=""></a>
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<a href="https://trendshift.io/repositories/7423" target="_blank"><img src="https://trendshift.io/api/badge/repositories/7423" alt="MobileAgent | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
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<a href="README_zh.md">简体中文</a> | <a href="README.md">English</a> | <a href="README_ja.md">日本語</a>
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## 📺Demo

### Mobile-Agent-v3（注意：该视频没有加速处理）
**YouTube**

[![YouTube](https://img.youtube.com/vi/EMbIpzqJld0/0.jpg)](https://www.youtube.com/watch?v=EMbIpzqJld0)

**哔哩哔哩**

[![Bilibili](https://img.youtube.com/vi/EMbIpzqJld0/0.jpg)](https://www.bilibili.com/video/BV1pPvyekEsa/?share_source=copy_web&vd_source=47ffcd57083495a8965c8cdbe1a751ae)

### PC-Agent
**谷歌浏览器与钉钉**

https://github.com/user-attachments/assets/b890a08f-8a2f-426d-9458-aa3699185030

**Word**

https://github.com/user-attachments/assets/37f0a0a5-3d21-4232-9d1d-0fe845d0f77d

### Mobile-Agent-v2
https://github.com/X-PLUG/MobileAgent/assets/127390760/d907795d-b5b9-48bf-b1db-70cf3f45d155

### Mobile-Agent
https://github.com/X-PLUG/MobileAgent/assets/127390760/26c48fb0-67ed-4df6-97b2-aa0c18386d31

## 📢新闻
* 🔥🔥[9.26] Mobile-Agent-v2 被 **The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)** 接收。
* 🔥[8.23]我们发布了一个支持Mac和Windows平台的**PC**操作助手PC-Agent, 通过Mobile-Agent-v2框架实现。
* 🔥[7.29] Mobile-Agent获得了 ***第二十三届中国计算语言学大会*** (CCL 2024) 的 **最佳demo奖项**。在CCL 2024上，我们展示了即将开源的Mobile-Agent-v3，拥有更小的内存开销（8 GB）、更快的推理速度（每次操作10-15秒），并且使用开源模型。视频Demo请见上一个板块📺Demo。
* [6.27] 我们在[Hugging Face](https://huggingface.co/spaces/junyangwang0410/Mobile-Agent)和[ModelScope](https://modelscope.cn/studios/wangjunyang/Mobile-Agent-v2)发布了可以上传手机截图体验Mobile-Agent-v2的Demo，无需配置模型和设备，即刻便可体验。
* [6. 4] Modelscope-Agent 已经支持 Mobile-Agent-V2，基于 Android Adb Env，请查看 [application](https://github.com/modelscope/modelscope-agent/tree/master/apps/mobile_agent)。
* [6. 4] 我们发布了新一代移动设备操作助手 Mobile-Agent-v2, 通过多智能体协作实现有效导航。
* [3.10] Mobile-Agent 被 **ICLR 2024 Workshop on Large Language Model (LLM) Agents** 接收。

## 📱版本
* [Mobile-Agent-v3](Mobile-Agent-v3/README_zh.md)
* [Mobile-Agent-v2](Mobile-Agent-v2/README_zh.md) - 通过多代理协作有效导航的移动设备操作助手
* [Mobile-Agent](Mobile-Agent/README_zh.md) - 视觉感知方案的自动化移动设备操作智能体

## ⭐Star历史
[![Star History Chart](https://api.star-history.com/svg?repos=X-PLUG/MobileAgent&type=Date)](https://star-history.com/#X-PLUG/MobileAgent&Date)

## 引用
If you find Mobile-Agent useful for your research and applications, please cite using this BibTeX:
```
@article{wang2024mobile2,
  title={Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration},
  author={Wang, Junyang and Xu, Haiyang and Jia Haitao and Zhang Xi and Yan, Ming and Shen, Weizhou and Zhang, Ji and Huang, Fei and Sang, Jitao},
  journal={arXiv preprint arXiv:2406.01014},
  year={2024}
}

@article{wang2024mobile,
  title={Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception},
  author={Wang, Junyang and Xu, Haiyang and Ye, Jiabo and Yan, Ming and Shen, Weizhou and Zhang, Ji and Huang, Fei and Sang, Jitao},
  journal={arXiv preprint arXiv:2401.16158},
  year={2024}
}
```

## 📦相关项目
* [AppAgent: Multimodal Agents as Smartphone Users](https://github.com/mnotgod96/AppAgent)
* [mPLUG-Owl & mPLUG-Owl2: Modularized Multimodal Large Language Model](https://github.com/X-PLUG/mPLUG-Owl)
* [Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond](https://github.com/QwenLM/Qwen-VL)
* [GroundingDINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection](https://github.com/IDEA-Research/GroundingDINO)
* [CLIP: Contrastive Language-Image Pretraining](https://github.com/openai/CLIP)

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