Update README.md

README.md

@@ -9,7 +9,7 @@ tags:
 
 <!-- Provide a quick summary of what the model is/does. -->
 This model is a 3D VAE that encodes video into a compact latent space conditioned on a content frame. It compresses a video by a factor of \\(\frac{T}{4}\times\frac{H}{32}\times\frac{W}{32}\\), enabling 4096x downsampling.
-It is part of the [Reducio-DiT](https://arxiv.org/abs/xxxx), which is a video generation method. Codebase available [here](https://github.com/microsoft/Reducio-VAE).
+It is part of the [Reducio-DiT](https://arxiv.org/abs/2411.13552), which is a video generation method. Codebase available [here](https://github.com/microsoft/Reducio-VAE).
 
 
 ## Model Details
@@ -19,7 +19,7 @@ It is part of the [Reducio-DiT](https://arxiv.org/abs/xxxx), which is a video ge
 <!-- Provide the basic links for the model. -->
 
 - **Repository:** [GitHub Repository](https://github.com/microsoft/Reducio-VAE)
-- **Paper:** [arXiv](https://arxiv.org/abs/xxxx)
+- **Paper:** [arXiv](https://arxiv.org/abs/2411.13552)
 
 ## Uses
 
@@ -62,7 +62,7 @@ Metrics on 1K Pexels validation set and UCF-101:
 @article{tian2024reducio,
       title={REDUCIO! Generating 1024*1024 Video within 16 Seconds using Extremely Compressed Motion Latents}, 
       author={Tian, Rui and Dai, Qi and Bao, Jianmin and Qiu, Kai and Yang, Yifan and Luo, Chong and Wu, Zuxuan and Jiang, Yu-Gang},
-      journal={arXiv preprint arXiv:xxxx},
+      journal={arXiv preprint arXiv:2411.13552},
       year={2024}
 }
 ```