arXiv 2610.26837 · cs.CV · 2026-10-19
SpecKCast: Spectral Kalman Forecasting for Diffusion Acceleration
Javad Rajabi, Hakki Can Karaimer, David B. Lindell, Babak Taati, Michael S. Brown
Samsung Research
在最新榜 #307 本站收录于 2026-10-22
一句话要点
SpecKCast 在频域用卡尔曼滤波预测扩散 Transformer 输出,不确定性高时才真算一次,无需训练即可加速。
SpecKCast forecasts DiT outputs in the frequency domain with Kalman filters, running the model only when uncertainty is high, for training-free speedup.
阅读 arXiv 原文 PDF Hugging Face 讨论 项目页
主题与学科
同主题:视觉生成
- MaLiang-Harness: A Programmable Path to Image and Video Generation ▲367
- Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation ▲364
- DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion Models ▲325
- UltraText Bench: A Comprehensive Bilingual Benchmark for Evaluating Visual Text Rendering in Image Generation ▲197
- Matrix-Game 4.0: Harnessing Video Models for Real-Time Playable Game Worlds ▲182
数据说明
元数据来自 arXiv API(已核实);点赞来自 Hugging Face 每日论文;引用来自 Semantic Scholar。最近刷新 2026-10-22。
要点由本站根据摘要自写,不转载摘要原文,请阅读原文。 要点修订于 2026-10-22。