Hugging Face Trending Papers
LinCa: Accelerating Diffusion Models via Learnable Decomposed Feature Caching
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arXiv Machine Learning
Jun 26
LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration
arXiv:2606. 26778v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) have driven substantial progress in image and video generation but suffer from prohibitive computational costs.
Hugging Face Trending Papers
Jul 26
OmniCache: Multidimensional Hierarchical Feature Caching For Diffusion Models
High-resolution image and video diffusion models, including SD3, FLUX, and recent video diffusion transformers, have substantially improved generative quality but remain expensive at inference time because they repeatedly evaluate attention-heavy denoisers over many sampling steps. We address this inefficiency by exploiting redundancy in intermediate diffusion features rather than changing model weights or retraining.
arXiv Machine Learning
Jul 31
FeatFix: Reuse What You Verify through Local Exact-Feature Correction for Faster Cached Diffusion Inference
arXiv:2607. 27842v1 Announce Type: cross Abstract: Diffusion models are widely used to generate high-quality images and videos, but their iterative denoising process remains computationally intensive.
arXiv Computer Vision
Oct 1
Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration
arXiv:2603.01623v2 Announce Type: replace Abstract: Diffusion models have become the dominant tool for high-fidelity image and video generation, yet are critically bottlenecked by their inference spe...
arXiv Computer Vision
Oct 8
MORCA: Offline-to-Online Reinforcement Learning for Adaptive Cache Reuse in Video Diffusion Acceleration
arXiv:2610.10457v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve remarkable performance in video synthesis, but their iterative denoising process suffers from high inference late...
arXiv Machine Learning
Sep 22
SenCache: Accelerating Diffusion Model Inference via Sensitivity-Aware Caching
arXiv:2602.24208v2 Announce Type: replace-cross Abstract: Diffusion models achieve state-of-the-art video generation quality, but their inference remains expensive due to the large number of sequenti...