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arXiv 2610.06801 · cs.CV · 2026-10-05

MC-Sparse: Deconstructing and Closing the Dense-Sparse Attention Gap in Diffusion Transformers

Jiarui Chen, Zeqiang Lai, Jiangshan Wang, Ziheng Ouyang, Ye Huang, Xiangyu Yue, Cewu Lu, Chunchao Guo

Tencent Hunyuan

In latest · #179 Added on 2026-10-21

One-line takeaway

MC-Sparse is training-free sparse attention that selects individual KV tokens with cached compensation, closing the dense-sparse gap in DiTs.

MC-Sparse 免训练地逐个挑选 KV token 并缓存补偿,缩小扩散 Transformer 稀疏与稠密注意力的质量差。

46HF upvotes
46GitHub stars
0Citations (Semantic Scholar)
53.8Buzz score

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Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.

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