9 citations · 10 across the 7 of their papers we have counts for
5 papers · 1 filter
Mechanized Noninterference for Gradual Security
Tianyu Chen, Jeremy G. Siek
This paper presents the first machine-checked proof of noninterference for a language with gradual information-flow control, thereby establishing a rock solid foundation for secure…
BadRes: Reveal the Backdoors through Residual Connection
Mingrui He, Tianyu Chen, Haoyi Zhou +2
Generally, residual connections are indispensable network components in building CNNs and Transformers for various downstream tasks in CV and VL, which encourages skip shortcuts be…
MoEC: Mixture of Expert Clusters
Yuan Xie, Shaohan Huang, Tianyu Chen +1
Sparsely Mixture of Experts (MoE) has received great interest due to its promising scaling capability with affordable computational overhead. MoE converts dense layers into sparse…
Task-Specific Expert Pruning for Sparse Mixture-of-Experts
Tianyu Chen, Shaohan Huang, Yuan Xie +5
The sparse Mixture-of-Experts (MoE) model is powerful for large-scale pre-training and has achieved promising results due to its model capacity. However, with trillions of paramete…
THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption
Tianyu Chen, Hangbo Bao, Shaohan Huang +6
As more and more pre-trained language models adopt on-cloud deployment, the privacy issues grow quickly, mainly for the exposure of plain-text user data (e.g., search history, medi…