How does one find top k embedding vectors such that they are similar to one particular vector and dissimilar to another?

A question on AI Stack Exchange asks how to find the top k embedding vectors that are similar to one vector A and dissimilar to another vector B, proposing a scoring function that subtracts the cosine similarity to B from the cosine similarity to A.

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