A survey on resource management in joint communication and computing-embedded SAGIN
The advent of the 6G era aims for ubiquitous connectivity, with the integration of non-
terrestrial networks (NTN) offering extensive coverage and enhanced capacity. As …
terrestrial networks (NTN) offering extensive coverage and enhanced capacity. As …
Efficient parallel split learning over resource-constrained wireless edge networks
The increasingly deeper neural networks hinder the democratization of privacy-enhancing
distributed learning, such as federated learning (FL), to resource-constrained devices. To …
distributed learning, such as federated learning (FL), to resource-constrained devices. To …
Adaptsfl: Adaptive split federated learning in resource-constrained edge networks
The increasing complexity of deep neural networks poses significant barriers to
democratizing them to resource-limited edge devices. To address this challenge, split …
democratizing them to resource-limited edge devices. To address this challenge, split …
Automated federated pipeline for parameter-efficient fine-tuning of large language models
Recently, there has been a surge in the development of advanced intelligent generative
content (AIGC), especially large language models (LLMs). However, for many downstream …
content (AIGC), especially large language models (LLMs). However, for many downstream …
SplitLoRA: A split parameter-efficient fine-tuning framework for large language models
Z Lin, X Hu, Y Zhang, Z Chen, Z Fang, X Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
The scalability of large language models (LLMs) in handling high-complexity models and
large-scale datasets has led to tremendous successes in pivotal domains. While there is an …
large-scale datasets has led to tremendous successes in pivotal domains. While there is an …
Satsense: Multi-satellite collaborative framework for spectrum sensing
Low Earth Orbit satellite Internet has recently been deployed, providing worldwide service
with non-terrestrial networks. With the large-scale deployment of both non-terrestrial and …
with non-terrestrial networks. With the large-scale deployment of both non-terrestrial and …
AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning
Connected and autonomous driving is developing rapidly in recent years. However, current
autonomous driving systems, which are primarily based on data-driven approaches, exhibit …
autonomous driving systems, which are primarily based on data-driven approaches, exhibit …
FedAC: A Adaptive Clustered Federated Learning Framework for Heterogeneous Data
Y Zhang, H Chen, Z Lin, Z Chen, J Zhao - arXiv preprint arXiv:2403.16460, 2024 - arxiv.org
Clustered federated learning (CFL) is proposed to mitigate the performance deterioration
stemming from data heterogeneity in federated learning (FL) by grouping similar clients for …
stemming from data heterogeneity in federated learning (FL) by grouping similar clients for …
Accelerating Handover in Mobile Satellite Network
The construction of Low Earth Orbit (LEO) satellite constellations has recently spurred
tremendous attention from academia and industry. 5G and 6G standards have specified LEO …
tremendous attention from academia and industry. 5G and 6G standards have specified LEO …
Satellite Federated Edge Learning: Architecture Design and Convergence Analysis
The proliferation of low-earth-orbit (LEO) satellite networks leads to the generation of vast
volumes of remote sensing data which is traditionally transferred to the ground server for …
volumes of remote sensing data which is traditionally transferred to the ground server for …