VDE accelerates rectified flow models like Flux by 3.22x with LPIPS of 0.069 via velocity decomposition into parallel/orthogonal components plus periodic full-pass anchoring.
Consistency models
3 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
L2P trains per-timestep linear weights on feature trajectories in about 20 seconds to enable aggressive caching in DiT models, delivering up to 4.55x FLOPs reduction with maintained visual quality.
Stabilizes MeanFlow for large-scale diffusion distillation via discrete warm-up and trajectory alignment, reporting better results on FLUX.1-dev and HunyuanImage 3.0.
citing papers explorer
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VDE: Training-Free Accelerating Rectified Flow Model via Velocity Decomposition and Estimation
VDE accelerates rectified flow models like Flux by 3.22x with LPIPS of 0.069 via velocity decomposition into parallel/orthogonal components plus periodic full-pass anchoring.
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Beyond Fixed Formulas: Data-Driven Linear Predictor for Efficient Diffusion Models
L2P trains per-timestep linear weights on feature trajectories in about 20 seconds to enable aggressive caching in DiT models, delivering up to 4.55x FLOPs reduction with maintained visual quality.
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Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation
Stabilizes MeanFlow for large-scale diffusion distillation via discrete warm-up and trajectory alignment, reporting better results on FLUX.1-dev and HunyuanImage 3.0.