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Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption
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Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption
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Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption
Announce Type: replace Abstract: Many NLP or recommendation models begin by mapping discrete client inputs to embedding vectors. Since inputs can reveal sensitive information, the embedding step must be protected in privacy-preserving inference. Fully Homomorphic Encryption (FHE) enables inference over encrypted client data, but turns embedding lookup from simple table access into homomorphic computation.