Radial Attention

[NeurIPS 2025] Radial Attention: O(nlogn) Sparse Attention with Energy Decay for Long Video Generation

AI Video CreationOpen Source AI & Machine LearningOpen Source

About

Radial Attention is a scalable sparse attention mechanism that enhances video diffusion models by achieving O(n log n) computational complexity. It utilizes physics-inspired sparsity to enforce spatially local and temporally decaying attention, which mirrors energy dissipation in physical systems. This approach allows for the efficient generation of longer videos while maintaining high quality, making it suitable for applications in video generation and processing.

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607
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34
License
Apache-2.0
Last commit
11 months ago
Python

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Vendor

MIT HAN Lab

Efficient AI Computing. PI: Song Han

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