research
∙
04/07/2023
Does Prompt-Tuning Language Model Ensure Privacy?
Prompt-tuning has received attention as an efficient tuning method in th...
share
research
∙
01/15/2023
UN Handbook on Privacy-Preserving Computation Techniques
This paper describes privacy-preserving approaches for the statistical a...
research
∙
12/16/2022
Planting and Mitigating Memorized Content in Predictive-Text Language Models
Language models are widely deployed to provide automatic text completion...
research
∙
01/20/2021
Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation
Homomorphic encryption, secure multi-party computation, and differential...
research
∙
08/10/2020
Trustworthy AI Inference Systems: An Industry Research View
In this work, we provide an industry research view for approaching the d...
research
∙
12/27/2019
EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation
Fully-Homomorphic Encryption (FHE) offers powerful capabilities by enabl...
research
∙
09/20/2019
HEAX: High-Performance Architecture for Computation on Homomorphically Encrypted Data in the Cloud
With the rapid increase in cloud computing, concerns surrounding data pr...
research
∙
09/20/2019
HEAX: An Architecture for Computing on Encrypted Data
With the rapid increase in cloud computing, concerns surrounding data pr...
research
∙
08/19/2019
PrivFT: Private and Fast Text Classification with Homomorphic Encryption
Privacy and security have increasingly become a concern for computing se...
research
∙
02/19/2019
XONN: XNOR-based Oblivious Deep Neural Network Inference
Advancements in deep learning enable cloud servers to provide inference-...
research
∙
10/01/2018