Attention Residuals: Kimi paper as an animated explainer
By Kimi (Moonshot AI) (@Kimi_Moonshot). Model: Kimi K3. Posted Sep 4, 2026. Original post: https://www.kimi.ai/showcases/deep-research/attention-residuals-interactive-demo
Build an English single-file interactive explainer for the Kimi team paper Attention Residuals. For readers with a deep-learning background: first animate the depth-dilution problem of PreNorm residual accumulation (hidden-state magnitude grows with depth and early layers get diluted), then explain Full AttnRes, where a learnable pseudo-query attends over all previous layer outputs with softmax weights, and finally land on Block AttnRes with its two-phase computation (plain residuals inside a block, attention across blocks), closing with a comparison of memory and communication costs. Render formulas with KaTeX (fall back to raw LaTeX text if the CDN fails), section navigation, adjustable animation speed, clean academic layout, single self-contained HTML file that works offline.
