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
In latest · #307 Added on 2026-10-22
One-line takeaway
SpecKCast forecasts DiT outputs in the frequency domain with Kalman filters, running the model only when uncertainty is high, for training-free speedup.
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。
Read on arXiv PDF Hugging Face discussion Project page
Topics & disciplines
More on Visual generation
- 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
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original. Takeaway revised on 2026-10-22.