#recommendation

2 articles

01 ·Inference & Serving·★ MEMBER·PAPER·6 min read Paper Explained: IntBMoE — Every Expert Contributes, Yet Each Token Runs Only a Few Blocks In a Mixture-of-Experts layer, how many experts inform a token, how many get computed, and how many weight sets must be built have always been tied together. IntBMoE (arXiv:2609.21346) cuts those ties by composing experts densely and executing blocks sparsely. Explained from scratch, using only the paper itself. 02 ·Deep Learning Basics·★ MEMBER·PAPER·12 min read Graph Neural Networks from Scratch — Learning from Connections Social networks, molecules and road maps are all built from dots and lines. This piece builds message passing up from nothing, explains why stacking layers makes every node look identical (over-smoothing), and follows the idea through to how recommenders and drug discovery actually use it.