SSOG Challenges SDPA in ViTs, Offering Faster Convergence and Near-Linear Scaling
serrjoa · x · 2026-08-17
Argues that Scaled Dot-Product Attention (SDPA) is suboptimal for Vision Transformers (ViTs). Introduces SSOG (Separable Sum Of Gaussians), which achieves faster convergence, better performance, and near-linear scaling capabilities.
More from Research
- TSUI: Native UI Framework Compiling TS/XML to GPU — johnlindquist · 2026-08-24
- Anthropic Study: Fine-Tuned Lie Detectors Fail to Generalize OOD — PandaAshwinee · 2026-08-24
- Shengshu Tech Unveils 5-Stage Roadmap for General World Models — 生数科技 · 2026-08-24
- AGI May Arrive First in Hard Tech Due to Objective Feedback Loops — imjustnewatai · 2026-08-24
- Trained a 1.57B-parameter Dreamer 4 World Model from scratch for under $150 — OtherRaisin3426 · 2026-08-24
- Graph Engineering organizes multi-agent systems via dynamic structures — Yuyuan Feng · 2026-08-24