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SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC
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SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC

Jinglong Luo
Yehong Zhang
Zhuo Zhang
Jiaqi Zhang
Xin Mu
Hui Wang
Yue Yu
Zenglin Xu
ArXiv (abs)PDFHTML

Papers citing "SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC"

4 / 4 papers shown
Title
Private Transformer Inference in MLaaS: A Survey
Private Transformer Inference in MLaaS: A Survey
Yang Li
Xinyu Zhou
Yun Wang
Liangxin Qian
Jun Zhao
68
0
0
15 May 2025
A Survey on Privacy Risks and Protection in Large Language Models
A Survey on Privacy Risks and Protection in Large Language Models
Kang Chen
Xiuze Zhou
Yuanguo Lin
Shibo Feng
Li Shen
Pengcheng Wu
AILawPILM
450
0
0
04 May 2025
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private Large Language Model Inference
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private Large Language Model Inference
Wenxuan Zeng
Ye Dong
Jinjin Zhou
Junming Ma
Jin Tan
Runsheng Wang
Meng Li
106
0
0
12 Jan 2025
Privacy in Large Language Models: Attacks, Defenses and Future Directions
Privacy in Large Language Models: Attacks, Defenses and Future Directions
Haoran Li
Yulin Chen
Jinglong Luo
Yan Kang
Xiaojin Zhang
Qi Hu
Chunkit Chan
Yangqiu Song
PILM
118
45
0
16 Oct 2023

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