Update README.md

Author: junyangwang0410

README.md

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 ## 📢News
 
-- `[2025.10.30]`🔥🔥 We released **OSWorld-MCP**, which is a benchmark for evaluating Model Context Protocol (MCP) tool invocation capabilities in real-world scenarios. See the [Link](https://github.com/X-PLUG/OSWorld-MCP).
+- `[2025.11.25]`🔥🔥 The GUI-Owl series models are now available for online inference, thanks to **Alibaba Cloud Bailian** for providing computing power support. Please refer to the [Link](https://modelscope.cn/models/iic/GUI-Owl-7B).
+- `[2025.10.30]`🔥 We released **OSWorld-MCP**, which is a benchmark for evaluating Model Context Protocol (MCP) tool invocation capabilities in real-world scenarios. See the [Link](https://github.com/X-PLUG/OSWorld-MCP).
 - `[2025.9.24]`🔥 We've released the demo on ModelScope that's based on Wuying Cloud Desktop and Phone. No need to deploy models locally or prepare devices, just input your instruction to experience Mobile-Agent-v3! [<img src="./assets/tongyi.png" width="14px" style="display:inline;"> ModelScope Demo Link](https://modelscope.cn/studios/wangjunyang/Mobile-Agent-v3) and [<img src="./assets/aliyun.png" width="14px" style="display:inline;"> Bailian Demo Link](https://bailian.console.aliyun.com/next?tab=demohouse#/experience/adk-computer-use/pc). For a limited-time free Mobile-Agent-v3 API, please check the [documentation](https://help.aliyun.com/zh/model-studio/ui-agent-api). The new version based on Qwen-3-VL is coming soon.
-- `[2025.9.19]`🔥 GUI-Critic-R1 has been accepted by **The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)**. 
-- `[2025.9.16]`🔥 We have released our latest work, **UI-S1: Advancing GUI Automation via Semi-online Reinforcement Learning**. The [paper](https://www.arxiv.org/abs/2509.11543), [code](https://github.com/X-PLUG/MobileAgent/tree/main/UI-S1), [dataset](https://huggingface.co/datasets/mPLUG/UI_S1_dataset) and [model](https://huggingface.co/mPLUG/UI-S1-7B) are now open-sourced.
+- `[2025.9.19]` GUI-Critic-R1 has been accepted by **The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)**. 
+- `[2025.9.16]` We have released our latest work, **UI-S1: Advancing GUI Automation via Semi-online Reinforcement Learning**. The [paper](https://www.arxiv.org/abs/2509.11543), [code](https://github.com/X-PLUG/MobileAgent/tree/main/UI-S1), [dataset](https://huggingface.co/datasets/mPLUG/UI_S1_dataset) and [model](https://huggingface.co/mPLUG/UI-S1-7B) are now open-sourced.
 - `[2025.9.16]` We've open-sourced the code of GUI-Owl and Mobile-Agent-v3 on OSWorld, AndroidWorld, and real-world mobile scenarios. See the [OSWorld Code](https://github.com/X-PLUG/MobileAgent/tree/main/Mobile-Agent-v3#evaluation-on-osworld). The OSWorld RL-tuned [checkpoint](https://huggingface.co/mPLUG/GUI-Owl-7B-Desktop-RL) of GUI-Owl is also released. See the [AndroidWorld Code](https://github.com/X-PLUG/MobileAgent/tree/main/Mobile-Agent-v3#evaluation-on-androidworld) and [Real-world Scenarios Code](https://github.com/X-PLUG/MobileAgent/tree/main/Mobile-Agent-v3#deploy-mobile-agent-v3-on-your-mobile-device).
 - `[2025.8.20]`All new **GUI-Owl** and **Mobile-Agent-v3** are released! Technical report can be found [here](https://arxiv.org/abs/2508.15144). And model checkpoint will be released on [GUI-Owl-7B](https://huggingface.co/mPLUG/GUI-Owl-7B) and [GUI-Owl-32B](https://huggingface.co/mPLUG/GUI-Owl-32B).
   - GUI-Owl is a multi-modal cross-platform GUI VLM with GUI perception, grounding, and end-to-end operation capabilities.