Update README.md

README.md

@@ -4,6 +4,9 @@ license: mit
 
 # Delving into Latent Spectral Biasing of Video VAEs for Superior Diffusability
 
+[![Website](https://img.shields.io/badge/Website-Project%20Page-blue)](https://zhazhan.github.io/ssvae.github.io)
+[![arXiv](https://img.shields.io/badge/arXiv-2512.05394-b31b1b)](https://arxiv.org/abs/2512.05394)
+
 
 Most existing video VAEs prioritize reconstruction fidelity, often overlooking the latent structure's impact on
 downstream diffusion training. Our research identifies properties of video VAE latent spaces that facilitate diffusion
@@ -31,4 +34,20 @@ to improved diffusability. Motivated by this, we introduce **SSVAE (Spectral-Str
 
 ## Using Model
 
-Please View our [Github](https://github.com/zai-org/SSVAE).
+Please View our [Github](https://github.com/zai-org/SSVAE).
+
+## Citation
+
+If you find this work useful in your research, please consider citing:
+
+```bibtex
+@misc{liu2025delvinglatentspectralbiasing,
+      title={Delving into Latent Spectral Biasing of Video VAEs for Superior Diffusability}, 
+      author={Shizhan Liu and Xinran Deng and Zhuoyi Yang and Jiayan Teng and Xiaotao Gu and Jie Tang},
+      year={2025},
+      eprint={2512.05394},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2512.05394}, 
+}
+```