docs: update README

README.md

@@ -97,7 +97,9 @@ For enterprises interested in adopting SVDQuant or Nunchaku, including technical
 - [DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models](https://arxiv.org/abs/2402.19481), CVPR 2024
 - [QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving](https://arxiv.org/abs/2405.04532), MLSys 2025
 - [SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers](https://arxiv.org/abs/2410.10629), ICLR 2025
-- [Radial Attention: $O(n \log n)$ Sparse Attention with Energy Decay for Long Video Generation](https://github.com/mit-han-lab/radial-attention), ArXiv 2025
+- [Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity](https://arxiv.org/abs/2502.01776), ICML 2025
+- [Radial Attention: $O(n \log n)$ Sparse Attention with Energy Decay for Long Video Generation](https://github.com/mit-han-lab/radial-attention), NeurIPS 2025
+- [Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation](https://arxiv.org/abs/2505.18875), NeurIPS 2025
 
 ## Citation