4 citations · 11 across the 7 of their papers we have counts for
7 papers
Towards Secure Semantic Communications in the Presence of Intelligent Eavesdroppers
Shunpu Tang, Yuhao Chen, Qianqian Yang +3
Semantic communication has emerged as a promising paradigm for enhancing communication efficiency in sixth-generation (6G) networks. However, the broadcast nature of wireless chann…
A Review on Edge Large Language Models: Design, Execution, and Applications
Yue Zheng, Yuhao Chen, Bin Qian +3
Large language models (LLMs) have revolutionized natural language processing with their exceptional understanding, synthesizing, and reasoning capabilities. However, deploying LLMs…
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…
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…
The Model Inversion Eavesdropping Attack in Semantic Communication Systems
Yuhao Chen, Qianqian Yang, Zhiguo Shi +1
In recent years, semantic communication has been a popular research topic for its superiority in communication efficiency. As semantic communication relies on deep learning to extr…
Demo: low-power communications based on RIS and AI for 6G
Mingyao Cui, Zidong Wu, Yuhao Chen +3
Ultra-massive multiple-input-multiple-output (UM-MIMO) is promising to meet the high rate requirements for future 6G. However, due to the large number of antennas and high path los…
FTPipeHD: A Fault-Tolerant Pipeline-Parallel Distributed Training Framework for Heterogeneous Edge Devices
Yuhao Chen, Qianqian Yang, Shibo He +2
With the increased penetration and proliferation of Internet of Things (IoT) devices, there is a growing trend towards distributing the power of deep learning (DL) across edge devi…