Blog reframes sparse and linear attention with a Taylor expansion and second-order fix
CatAstro_Piyush · x · 2026-07-29
- A blog post reframes sparse and linear attention under one lens: a Taylor expansion view.
- It then extends the idea with a second-order correction (PWT), which the author says works both training-free and trainable.
- The post includes code and discusses why sparse attention matters for long-context LLMs and even more for video generation, where sequence lengths can become enormous.
More from Research
- Transforming quadruped robot runs on real hardware: per-pose RL policies in Isaac switched on morph — _Stocko_ · 2026-10-16
- KinoGen synthesizes robot loco-manipulation reference motions directly via kinematically grounded video generation — ChongZzZhang · 2026-10-16
- Science Robotics paper introduces F³, predictive event-based vision beyond optical flow — CSProfKGD · 2026-10-16
- VideoGen-Agent: An 8B Multimodal Agent Turns Video Generation Into a Tool-Use Loop — jiqizhixin · 2026-10-16
- Comprehension Audits: New Paper Proposes a Gate for AI-Written Code at Frontier Labs — ronbodkin · 2026-10-16
- Not Boring #215: Cammarata's Clean Networks Claim, Tesla's Flying Roadster, Tau Cut 73% — Not Boring (Packy McCormick) · 2026-10-16