Secure Transformer Inference Made Non-interactive

ePrint Report: Secure Transformer Inference Made Non-interactive

Jiawen Zhang, Jian Liu, Xinpeng Yang, Yinghao Wang, Kejia Chen, Xiaoyang Hou, Kui Ren, Xiaohu Yang

Secure transformer inference has emerged as a prominent research topic following the proliferation of ChatGPT. Existing solutions are typically interactive, involving substantial communication load and numerous interaction rounds between the client and the server.


In this paper, we propose NEXUS the first non-interactive protocol for secure transformer inference, where the client is only required to submit an …

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