13 citations · 26 across the 5 of their papers we have counts for
4 papers · 1 filter
EdgeMoE: Empowering Sparse Large Language Models on Mobile Devices
Rongjie Yi, Liwei Guo, Shiyun Wei +3
Large language models (LLMs) such as GPTs and Mixtral-8x7B have revolutionized machine intelligence due to their exceptional abilities in generic ML tasks. Transiting LLMs from dat…
Hierarchical Federated Learning through LAN-WAN Orchestration
Jinliang Yuan, Mengwei Xu, Xiao Ma +3
Federated learning (FL) was designed to enable mobile phones to collaboratively learn a global model without uploading their private data to a cloud server. However, exiting FL pro…
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
Chengxu Yang, Qipeng Wang, Mengwei Xu +4
Federated learning (FL) is an emerging, privacy-preserving machine learning paradigm, drawing tremendous attention in both academia and industry. A unique characteristic of FL is h…
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…