Private Embedding Lookup with Encrypted Compact Queries under Fully Homomorphic Encryption

Jung Hee Cheon, Daehyun Jang, Jaehee Kang +1

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…