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cs.CR2026
ROSETTA: Efficient and Accurate Privacy-Preserving LLM Decoding via Hybrid CKKS/TFHE Evaluation
Jiangrui Yu, Baosheng Zhang, Liang Kong +5
Generative large language models (LLMs) have achieved state-of-the-art performance on many real-world tasks such as code generation and question answering. These models predominant…
cs.CR2025
Breaking the Layer Barrier: Remodeling Private Transformer Inference with Hybrid CKKS and MPC
Tianshi Xu, Wen-jie Lu, Jiangrui Yu +4
This paper presents an efficient framework for private Transformer inference that combines Homomorphic Encryption (HE) and Secure Multi-party Computation (MPC) to protect data priv…