SQuad reduces video generation attention compute by 67x with O(N√N) complexity
jm_alexia · x · 2026-08-19
The paper introduces SQuad, a framework achieving O(N√N) complexity for Self-Attention in video generation. Using a two-stage distillation process on the Wan 2.2 5B model, it matches the quadratic teacher's quality on VBench (83.20 vs 83.08) while cutting attention FLOPs by 67x and latency by 11x per step per block.
More from Multimodal
- Paper: Strand-Based Hairstyle Generation via Large Reconstruction and Multimodal Models — ssh4net · 2026-08-19
- NVIDIA's RGBX-Next: diffusion models as learned renderers, speculated as DLSS 5 — ssh4net · 2026-08-19
- Comparison of image-to-video tools: Kling, Luma, and Runway — Manas_Patait · 2026-08-19
- Storyboard-based AI video demo features realistic water crossing — anthara_ai · 2026-08-19
- Can MiniMax H3's R2V Capability Be Used for Reference-to-Image? — ok-onwrap · 2026-08-19
- Creator uses Hailuo desktop agent to craft a spy-film title sequence with H3 — bennash · 2026-08-19