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arXiv Computer Vision By Haopeng Li, Shitong Shao, Wenliang Zhong, Zikai Zhou, Lichen Bai, Hui Xiong, Zeke Xie

PISA: Piecewise Sparse Attention Is Wiser for Efficient Diffusion Transformers

Read the original on arXiv Computer Vision →

PISA introduces a training‑free Piecewise Sparse Attention mechanism that preserves full attention span while reducing complexity. It keeps exact computation for critical blocks and approximates non‑critical ones using block‑wise Taylor expansion, avoiding the quality loss seen in conventional sparse attention. Experiments show significant speedups—up to 2.57× on Hunyuan‑Video—while maintaining or improving visual quality across video and image generation tasks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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