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Question

What do query, key and value mean in self-attention, according to Vizuara?

Answered from Q, K, V intuition - self attention with trainable weights | The attention family series - Lecture 6 · The attention family · 2026-09-18

In Vizuara's Lecture 6, Sreedath Panat defines the query as the token that is doing the attending and the key as the token being attended to; the value is what gets mixed into the output. All three are made from the same input embedding X by multiplying it with its own learned matrix: Q = X times W_Q, K = X times W_K and V = X times W_V. Attention scores come from queries dotted with keys, and the final context vector is a weighted sum of the values.

▸In their words

“Query is the token which is attending and key is the token that is being attended to.” Sreedath Panat · at 13:26 — open in the transcript →

Source: our own transcription of the episode. The full conversation is on The attention family (2026-09-18). Read the whole episode summary →

▸More from this episode

Q2Why can't self-attention use raw input embeddings for attention scores?Q3How does a key weight matrix change attention scores in Vizuara's dog and ball example?Q4What does an attention-weighted sum of value vectors mean in the transformer formula?Q5Can the query, key and value space have a different dimension from the input embeddings?Q6How are the W_Q, W_K and W_V weight matrices learned in an LLM?
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