Update README.md

README.md

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 # AccVideo: Accelerating Video Diffusion Model with Synthetic Dataset
 
-This repository contains the pre-trained weights of [AccVideo](). AccVideo is a novel efficient distillation method to accelerate video diffusion models with synthetic datset. Our method is 8.5x faster than HunyuanVideo.
+This repository contains the pre-trained weights of [AccVideo](https://arxiv.org/abs/2503.19462). AccVideo is a novel efficient distillation method to accelerate video diffusion models with synthetic datset. Our method is 8.5x faster than HunyuanVideo.
 
 
-[![arXiv](https://img.shields.io/badge/)]()[![Project Page](https://img.shields.io/badge/Project-Website-green)](https://aejion.github.io/accvideo/)
+[![arXiv](https://img.shields.io/badge/)](https://arxiv.org/abs/2503.19462)[![Project Page](https://img.shields.io/badge/Project-Website-green)](https://aejion.github.io/accvideo/)
 
 ## 🔥🔥🔥 News
 
@@ -71,10 +71,15 @@ The following table shows the comparisons on inference time using a single A100
 
 ## 🔗 BibTeX
 
-If you find [AccVideo]() useful for your research and applications, please cite using this BibTeX:
+If you find [AccVideo](https://arxiv.org/abs/2503.19462) useful for your research and applications, please cite using this BibTeX:
 
 ```BibTeX
-
+@article{zhang2025accvideo,
+    title={AccVideo: Accelerating Video Diffusion Model with Synthetic Dataset},
+    author={Zhang, Haiyu and Chen, Xinyuan and Wang, Yaohui and Liu, Xihui and Wang, Yunhong and Qiao, Yu},
+    journal={arXiv preprint arXiv:2503.19462},
+    year={2025}
+}
 ```
 
 ## Acknowledgements