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The authors thank Prof. Cong Wang of the City University of Hong Kong for his valuable suggestions on revising this paper
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Achieve near-plaintext LLM inference speeds with strong privacy guarantees and minimal accuracy loss by jointly obfuscating data and model parameters – a first for models at the 671B scale.
