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Video DeltaNet enhances video diffusion model efficiency with hybrid attention

By PulseAugur Editorial · [2 sources] ·

Researchers have developed Video DeltaNet (VDN), a novel approach to enhance the efficiency of video diffusion models. VDN addresses the computational bottleneck caused by attention mechanisms in processing long video sequences by integrating local Softmax attention with a bidirectional linear memory. This hybrid approach, featuring Video Delta Attention (VDA), updates memory once per frame, incorporating spatial tokens to maintain fine-grained interactions. When applied to the MiniMax H3 model, VDN achieved a significant speedup, reducing denoising time for a 14.3-second video from 50 steps to 6.70 seconds on eight NVIDIA B200 GPUs. AI

IMPACT This new method for video diffusion models could significantly speed up generation times, potentially enabling more complex and longer video content creation.

RANK_REASON The item describes a new research paper detailing a novel technical approach for video generation models. [lever_c_demoted from research: ic=1 ai=1.0]

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Video DeltaNet enhances video diffusion model efficiency with hybrid attention

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The item describes a new research paper detailing a novel technical approach for video generation models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Haocheng Xi, Yiming Xie, Hexu Zhao, Yiwen Zhang, Michael Liu, Thomas Creavin, Kurt Keutzer, Xiuyu Li, Zhaoyang Lv, Chenfeng Xu, Haiwen Feng ·

    Video DeltaNet: A Video-Native Hybrid Attention for Livestream Video Generation

    arXiv:2609.20744v1 Announce Type: new Abstract: Video diffusion models repeatedly process long spatiotemporal token sequences during denoising, making attention a major computational bottleneck. Linear attention offers an appealing alternative and has been widely adopted in recen…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Video DeltaNet: A Video-Native Hybrid Attention for Livestream Video Generation

    Video diffusion models repeatedly process long spatiotemporal token sequences during denoising, making attention a major computational bottleneck. Linear attention offers an appealing alternative and has been widely adopted in recent large language models, but directly applying i…

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