Parallax: A Parameterized Local Linear Attention That Keeps Softmax and Adds a Learned Covariance — 2026-06-01

Impact Vector: AI Tools · Jun 1, 2026 · 3m

## Short Segments Today on Impact Vector, we're diving into a new approach to AI efficiency that doesn't cut corners. We'll explore how Parallax, a parameterized Local Linear Attention, keeps the softmax intact while adding a novel correction branch. This development could reshape how large language models are trained and deployed. Stay tuned as we unpack the details and implications of this innovative method. ## Feature Story Parallax introduces a fresh perspective on AI efficiency by retaining the traditional softmax attention mechanism and enhancing it with a correction branch. This…