Can you fingerprint the embedding model from unordered retrieval results? Apparently yes, and the paper tests rerankers and RAG too.
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01 02 Can you keep dense retrieval useful after shredding embeddings into public prefixes and private CKKS shards? SHARD says maybe.03 Hybrid privacy-aware semantic search: SVD-truncated document geometry and CKKS-encrypted query reranking under a restricted threat model arxiv.orgHybrid semantic search paper: SVD-truncated docs plus CKKS query reranking, with the usual secure caveat that only half is cryptographic.04 Turns out the new trick is image prompts: passive black-box attacks reconstruct them from shared distributed MLLM embeddings, not just text.