37 citations · 92 across the 10 of their papers we have counts for
4 papers · 1 filter
A First Look at On-device Models in iOS Apps
Han Hu, Yujin Huang, Qiuyuan Chen +2
Powered by the rising popularity of deep learning techniques on smartphones, on-device deep learning models are being used in vital fields like finance, social media, and driving a…
Automated Mapping of Adaptive App GUIs from Phones to TVs
Han Hu, Ruiqi Dong, John Grundy +3
With the increasing interconnection of smart devices, users often desire to adopt the same app on quite different devices for identical tasks, such as watching the same movies on b…
ModelObfuscator: Obfuscating Model Information to Protect Deployed ML-based Systems
Mingyi Zhou, Xiang Gao, Jing Wu +4
More and more edge devices and mobile apps are leveraging deep learning (DL) capabilities. Deploying such models on devices -- referred to as on-device models -- rather than as rem…
Training-free Lexical Backdoor Attacks on Language Models
Yujin Huang, Terry Yue Zhuo, Qiongkai Xu +3
Large-scale language models have achieved tremendous success across various natural language processing (NLP) applications. Nevertheless, language models are vulnerable to backdoor…