activity
20232026
most citedFeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition

4 citations · 6 across the 8 of their papers we have counts for

collaborators
Showing 2023Show all

2 papers · 1 filter

cs.LG2023★ 2 cited

Confidant: Customizing Transformer-based LLMs via Collaborative Edge Training

Yuhao Chen, Yuxuan Yan, Qianqian Yang +3

Transformer-based large language models (LLMs) have demonstrated impressive capabilities in a variety of natural language processing (NLP) tasks. Nonetheless, it is challenging to…

cs.LG2023

AccEPT: An Acceleration Scheme for Speeding Up Edge Pipeline-parallel Training

Yuhao Chen, Yuxuan Yan, Qianqian Yang +4

It is usually infeasible to fit and train an entire large deep neural network (DNN) model using a single edge device due to the limited resources. To facilitate intelligent applica…