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Individual content and motion dynamics preserved pruning for video diffusion models.arXiv preprint arXiv:2411.18375, 2024

2 Pith papers cite this work. Polarity classification is still indexing.

2 Pith papers citing it

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cs.CV 2

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2026 2

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UNVERDICTED 2

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representative citing papers

Efficient Video Diffusion Models: Advancements and Challenges

cs.CV · 2026-04-17 · unverdicted · novelty 7.0

A survey that groups efficient video diffusion methods into four paradigms—step distillation, efficient attention, model compression, and cache/trajectory optimization—and outlines open challenges for practical use.

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Showing 2 of 2 citing papers.

  • Efficient Video Diffusion Models: Advancements and Challenges cs.CV · 2026-04-17 · unverdicted · none · ref 150

    A survey that groups efficient video diffusion methods into four paradigms—step distillation, efficient attention, model compression, and cache/trajectory optimization—and outlines open challenges for practical use.

  • PARE: Pruning and Adaptive Routing for Efficient Video Generation cs.CV · 2026-05-26 · unverdicted · none · ref 36

    PARE applies structure-aware head pruning and timestep/content-conditioned block routing to compress video DiTs, reducing per-step compute while preserving quality on Wan2.1-14B.