185 citations · 445 across the 25 of their papers we have counts for
4 papers · 1 filter
Federated Few-Shot Learning for Mobile NLP
Dongqi Cai, Shangguang Wang, Yaozong Wu +2
Natural language processing (NLP) sees rich mobile applications. To support various language understanding tasks, a foundation NLP model is often fine-tuned in a federated, privacy…
STI: Turbocharge NLP Inference at the Edge via Elastic Pipelining
Liwei Guo, Wonkyo Choe, Felix Xiaozhu Lin
Natural Language Processing (NLP) inference is seeing increasing adoption by mobile applications, where on-device inference is desirable for crucially preserving user data privacy…
FedAdapter: Efficient Federated Learning for Modern NLP
Dongqi Cai, Yaozong Wu, Shangguang Wang +2
Transformer-based pre-trained models have revolutionized NLP for superior performance and generality. Fine-tuning pre-trained models for downstream tasks often requires private dat…
A First Look at Deep Learning Apps on Smartphones
Mengwei Xu, Jiawei Liu, Yuanqiang Liu +3
We are in the dawn of deep learning explosion for smartphones. To bridge the gap between research and practice, we present the first empirical study on 16,500 the most popular Andr…