Update README.md

README.md

@@ -1,24 +1,62 @@
 ---
-library_name: <World Model>
-tags:
-  - Text-to-Video
-  - Image-to-Video
-  - Diffusion Video Model
-  - World Model
+
+
+
+
+
+
 license: apache-2.0
+pipeline_tag: image-to-video
+tags:
+- Text-to-Video
+- Image-to-Video
+- Diffusion Video Model
+- World Model
 ---
 
-# Yume: An Interactive World Generation Model
+# Yume-1.5: A Text-Controlled Interactive World Generation Model
 
-This is a preview version of the Yume model, an interactive world generation model, presented in the paper 
-[Yume: An Interactive World Generation Model](https://huggingface.co/papers/2507.17744) and [Yume-1.5: A Text-Controlled Interactive World Generation Model](
-https://arxiv.org/abs/2512.22096).
+Yume-1.5 is a framework designed to generate realistic, interactive, and continuous worlds from a single image or text prompt. It supports keyboard-based exploration of the generated environments through a framework that integrates context compression and real-time streaming acceleration.
 
-Yume aims to create an interactive, realistic, and dynamic world from an input image, allowing exploration and control.
 
-Project Page: [https://stdstu12.github.io/YUME-Project/](https://stdstu12.github.io/YUME-Project/)\
-GitHub Repository: [https://github.com/stdstu12/YUME](https://github.com/stdstu12/YUME)
+
+- [**Paper (Yume-1.5)**](https://huggingface.co/papers/2512.22096)
+- [**Paper (Yume-1.0)**](https://huggingface.co/papers/2507.17744)
+- [**Project Page**](https://stdstu12.github.io/YUME-Project/)
+- [**GitHub Repository**](https://github.com/stdstu12/YUME)
+
+## Features
+- **Long-video generation**: Unified context compression with linear attention.
+- **Real-time acceleration**: Powered by bidirectional attention distillation.
+- **Text-controlled events**: Method for generating specific world events via text prompts.
 
 ## Usage
 
-For detailed instructions and full inference scripts, please refer to the [GitHub repository](https://github.com/stdstu12/YUME).
+For detailed installation and setup instructions, please refer to the [GitHub repository](https://github.com/stdstu12/YUME). 
+
+### Inference Example
+To perform image-to-video generation using the provided scripts:
+
+```bash
+# Generate videos from images in the specified directory
+bash scripts/inference/sample_jpg.sh --jpg_dir="./jpg" --caption_path="./caption.txt"
+```
+
+## Citation
+
+If you use Yume for your research, please cite the following:
+
+```bibtex
+@article{mao2025yume,
+  title={Yume: An Interactive World Generation Model},
+  author={Mao, Xiaofeng and Lin, Shaoheng and Li, Zhen and Li, Chuanhao and Peng, Wenshuo and He, Tong and Pang, Jiangmiao and Chi, Mingmin and Qiao, Yu and Zhang, Kaipeng},
+  journal={arXiv preprint arXiv:2507.17744},
+  year={2025}
+}
+@article{mao2025yume,
+  title={Yume-1.5: A Text-Controlled Interactive World Generation Model},
+  author={Mao, Xiaofeng and Li, Zhen and Li, Chuanhao and Xu, Xiaojie and Ying, Kaining and He, Tong and Pang, Jiangmiao and Qiao, Yu and Zhang, Kaipeng},
+  journal={arXiv preprint arXiv:2512.22096},
+  year={2025}
+}
+```