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About this paper

Aleksandr Listopad

ResonanceDB extends vector embeddings by storing patterns with an amplitude and phase, then scoring matches through interference: aligned phases reinforce and opposing phases cancel. The authors compare it with cosine retrieval on a compact operator test using happy and good. For NEG, resonance achieves P@1 = 1.0 versus approximately 0.0 for cosine; this does not establish performance on natural language.

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