no code implementations • 2 Aug 2023 • Xiaobei Yan, Xiaoxuan Lou, Guowen Xu, Han Qiu, Shangwei Guo, Chip Hong Chang, Tianwei Zhang
One big concern about the usage of the accelerators is the confidentiality of the deployed models: model inference execution on the accelerators could leak side-channel information, which enables an adversary to preciously recover the model details.
1 code implementation • 19 May 2023 • Chaoqun Liu, Wenxuan Zhang, Guizhen Chen, Xiaobao Wu, Anh Tuan Luu, Chip Hong Chang, Lidong Bing
In this work, we propose a new paradigm based on self-supervised learning to solve zero-shot text classification tasks by tuning the language models with unlabeled data, called self-supervised tuning.