Private AI

PrivQuant: Communication-Efficient Private Inference with Quantized Network/Protocol Co-Optimization
Tianshi Xu, Shuzhang Zhong, Wenxuan Zeng, Runsheng Wang, Meng Li
Paper
FastQuery: Communication-efficient Embedding Table Query for Private LLMs inference
Chenqi Lin, Tianshi Xu, Zebin Yang, Meng Li, Runsheng Wang, Ru Huang
Paper
CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
A network–protocol co-optimization framework for reducing the communication overhead of secure private inference.
Wenxuan Zeng, Meng Li, Haichuan Yang, Wen-Jie Lu, Runsheng Wang, Ru Huang
Paper
Falcon: Accelerating Homomorphically Encrypted Convolutions for Efficient Private Mobile Network Inference
Tianshi Xu, Meng Li, Runsheng Wang, Ru Huang
Paper
MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention
Wenxuan Zeng, Meng Li, Wenjie Xiong, Tong Tong, Wen-Jie Lu, Jin Tan, Runsheng Wang, Ru Huang
Paper