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Transformer Attention Explained

How scaled dot-product attention lets models weigh which tokens matter — the core of GPT and modern AI.

9 min read · 2026-06-11

Attention(Q,K,V) = softmax(QKᵀ/√dₖ)V computes compatibility scores between queries and keys, then mixes value vectors.

Vaswani et al.'s 2017 paper replaced recurrence with attention, enabling parallel training at scale.

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