Large Language Models (LLMs) such as GPTs and LLaMa have ushered in a
re...
Deploying high-performance convolutional neural network (CNN) models on
...
Multi-task learning (MTL) seeks to learn a single model to accomplish
mu...
The on-orbit processing of massive satellite-native data relies on power...
Deploying high-performance vision transformer (ViT) models on ubiquitous...
Natural language processing (NLP) sees rich mobile applications. To supp...
Transformer-based pre-trained models have become the de-facto solution f...
Recent developments in the aerospace industry have led to a dramatic
red...
Nowadays, high-volume and privacy-sensitive data are generated by mobile...
This paper proposes Mandheling, the first system that enables highly
res...
DNNs are ubiquitous on edge devices nowadays. With its increasing import...
Transformer-based pre-trained models have revolutionized NLP for superio...
Space-air-ground integrated network (SAGIN) is a new type of wireless ne...
Satellite network is the first step of interstellar voyages. It can prov...
Mobile networks (MN) are anticipated to provide unprecedented opportunit...
Public edge platforms have drawn increasing attention from both academia...
Federated learning (FL) was designed to enable mobile phones to
collabor...
Federated learning (FL) is an emerging distributed machine learning para...
Mobile edge computing is beneficial to reduce service response time and ...
It is a big challenge for resource-limited mobile devices (MDs) to execu...
Crowd-intelligence tries to gather, process, infer and ascertain massive...
This article proposes an edge content delivery framework (ECD) based on
...