2 papers
cs.CR2025
An Efficient Private GPT Never Autoregressively Decodes
Zhengyi Li, Yue Guan, Kang Yang +5
The wide deployment of the generative pre-trained transformer (GPT) has raised privacy concerns for both clients and servers. While cryptographic primitives can be employed for sec…
cs.CR2024
Nimbus: Secure and Efficient Two-Party Inference for Transformers
Zhengyi Li, Kang Yang, Jin Tan +8
Transformer models have gained significant attention due to their power in machine learning tasks. Their extensive deployment has raised concerns about the potential leakage of sen…