Self-Attention is powerful. But by itself, it has three problems. It needs multiple views, it needs...
Self-Attention is powerful.
But by itself, it has three problems.
It needs multiple views, it needs word order, and it needs stable training.
That is why Multi-Head Attention, Positional Encoding, and Add & Norm exist.
Core Idea
Self-Attention can compare every token with every other token. But there is a catch. By itself, it...
Self-Attention is not just “looking at important words.” It is a matrix operation. And that is...
When people first hear about Transformers, they often encounter words like Query, Key, Value, and...
Transformers changed AI because they stopped reading sequences one token at a time. Instead of...
Originally published on my blog. Cross-posted here with a canonical link. Recap:...
Merging full‑attention and linear‑attention at the head granularity slashes transformer FLOPs without...
