RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation
arXiv:2607.02584v1 Announce Type: new Abstract: In \textbf{DiT-based video generation models equipped with 3D Rotary Position Embeddings (3D RoPE)}, the attention mechanism remains a primary computational bottleneck due to its quadratic complexity with respect to sequence length. While quantized \textbf{FlashAttention} offers a promising path toward hardware acceleration, existing low-bit quantization methods overlook two critical challenges in this setting: \textbf{1)} applying online rotation ...
arXiv cs.CV
·Yaofu Liu, Wanli Lan, Jinxi Li, Binhang Yuan, Harry Yang
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