Self-Attention
Self-attention is attention where queries, keys, and values all come from the same sequence, so each position can mix information from every other position in one layer.
Definition
Self-Attention refers to attention is attention where queries, keys, and values all come from the same sequence, so each position can mix information from every other position in one layer. Keep that definition fixed when comparing series, managers, or regimes — renaming the same tape does not create a new signal.
Why it matters
It binds model output to retrieval, tools, or evaluation so answers stay grounded instead of free-floating. When attention is attention where queries, keys, and values all come from the same sequence, so each position can mix information from every other position in one layer shifts, related hedges, limits, and narratives usually need an explicit update rather than a quiet assumption.
Case
Suppose a desk is positioned for the opposite of what self-attention is saying. If attention is attention where queries, keys, and values all come from the same sequence, so each position can mix information from every other position in one layer moves against that book, the first question is not “is the story clever?” but whether size, hedges, and stop logic still match the observation.
How to read it
Measure grounding rate, latency, and failure modes under missing context — not demo chat quality alone. Prefer a short written null hypothesis for Self-Attention: what would falsify the current reading in the next window?