Semantic Caching Is Not A Threshold Problem: Revision history

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3 November 2026

  • curprev 19:3619:36, 3 November 2026 DamionCrespin77 talk contribs 4,016 bytes +4,016 Created page with "<br>Semantic caching promises a simple win: store a large-language-model response, and when a new query arrives, compare its embedding to the stored query’s embedding. If the cosine similarity is high enough, return the old answer instead of calling the model again. In deployed products, that decision is governed by a single similarity threshold, typically shipped as a default between 0.80 and 0.95. The intuition is that anything above that range is a paraphrase, and a..."
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