← Back to all news
arXiv Machine Learning September 22, 2026 By Yasaman Haghighi, Alexandre Alahi

SenCache: Accelerating Diffusion Model Inference via Sensitivity-Aware Caching

Read the original on arXiv Machine Learning →

The Flow has not summarised this story yet — read it at arXiv Machine Learning.

  • diffusion
  • benchmarks

One email a morning, machine-written

One email a day, machine-written, one click to leave. We never share your address.

Related stories

arXiv AI
3d ago

The Golden Path Hypothesis: Reusable Schedules in Diffusion Caching

arXiv:2609.39343v1 Announce Type: new Abstract: Diffusion caching accelerates generation by replacing transformer computation with cached or predicted features at selected denoising steps. We introdu...

By Dong Wang, Wenwu Tang, Francesco Corti, Yun Cheng, Lothar Thiele, Olga Saukh
llmsdiffusion
More like this →
arXiv Machine Learning
Aug 3

OnlineCache: Learning Dynamic Caching Policies with Error Correction for Efficient Diffusion Inference

arXiv:2607. 29398v1 Announce Type: new Abstract: Diffusion models have revolutionized generative tasks but incur high latency due to iterative denoising.

By Zhikang Xie, Xichen Ye, Yifan Wu, Haoshen Yu, Li chenan, Peizhu Gong, Weizhong Zhang, Cheng Jin
diffusionreinforcement-learning
More like this →
arXiv AI
Sep 1

EpaCache: Error-Propagation-Aware Caching for Accelerating Diffusion-Based Visual Generation

arXiv:2608.29264v1 Announce Type: new Abstract: Diffusion-based visual generative models deliver strong image and video synthesis quality but incur high inference costs because sequential samplers re...

By Yuhan Liu, Zongwei Hong, Jinglun Li, Linze Li, Shen Zhang, Yao Tang
diffusionefficiencybenchmarks
More like this →
arXiv AI
Aug 14

From Local Mismatch to Global Impact: Optimizing Cache Reuse Policy for Efficient Diffusion

arXiv:2608. 13043v1 Announce Type: new Abstract: Diffusion models have achieved dominant performance in visual generation but suffer from substantial inference overhead.

By Xichen Ye, Yifan Wu, Zhikang Xie, Xiangyu Yue, Cheng Jin, Weizhong Zhang
diffusionbenchmarks
More like this →
arXiv AI
Jul 1

OTCache: Optimal Transport for Geometry-Aware Caching in Diffusion Models

arXiv:2606. 31026v1 Announce Type: cross Abstract: We propose OTCache, a training-free framework for accelerating diffusion sampling via caching schedule prediction.

By Huanlin Gao, Fang Zhao, Qiang Hui, Fuyuan Shi, Shaoan Zhao, Yantao Li, Chao Tan, Ting Lu, Yuren You, Kai Wang, Shiguo Lian
diffusionbenchmarks
More like this →
arXiv AI
Aug 6

AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers

arXiv:2602. 13357v3 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) achieve state-of-the-art performance in high-fidelity image and video generation but suffer from expensive inference due to their iterative denoising structure.

By Dong Liu, Yanxuan Yu, Ben Lengerich, Ying Nian Wu
llmsdiffusionbenchmarks
More like this →
About Pricing API Newsletter Sources Privacy Terms Refunds Accessibility Provider info Contact RSS

The Flow links to publishers and never republishes their articles. Summaries are machine-generated.

v1.1.0 · 5f852ea