1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CR2025
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference
Wenxuan Zeng, Ye Dong, Jinjin Zhou +5
Private large language model (LLM) inference based on secure multi-party computation (MPC) achieves formal data privacy protection but suffers from significant latency overhead, es…
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…
cs.CR2022★ 1 cited
MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention
Wenxuan Zeng, Meng Li, Wenjie Xiong +5
Secure multi-party computation (MPC) enables computation directly on encrypted data and protects both data and model privacy in deep learning inference. However, existing neural ne…