Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …
Pushing large language models to the 6g edge: Vision, challenges, and opportunities
Large language models (LLMs), which have shown remarkable capabilities, are
revolutionizing AI development and potentially shaping our future. However, given their …
revolutionizing AI development and potentially shaping our future. However, given their …
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 …
Vehicle as a service (VaaS): Leverage vehicles to build service networks and capabilities for smart cities
Smart cities demand resources for rich immersive sensing, ubiquitous communications,
powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of …
powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of …
Fedsn: A general federated learning framework over leo satellite networks
Recently, a large number of Low Earth Orbit (LEO) satellites have been launched and
deployed successfully in space by commercial companies, such as SpaceX. Due to …
deployed successfully in space by commercial companies, such as SpaceX. Due 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 …
D-JSCC: Digital Deep Joint Source-channel Coding for Semantic Communications
Semantic communications (SemCom) have emerged as a new paradigm for supporting sixth-
generation applications, where semantic features of data are transmitted using artificial …
generation applications, where semantic features of data are transmitted using artificial …
Optimal resource allocation for u-shaped parallel split learning
Split learning (SL) has emerged as a promising approach for model training without
revealing the raw data samples from the data owners. However, traditional SL inevitably …
revealing the raw data samples from the data owners. However, traditional SL inevitably …
Graph learning for multi-satellite based spectrum sensing
H Yuan, Z Chen, Z Lin, J Peng, Z Fang… - 2023 IEEE 23rd …, 2023 - ieeexplore.ieee.org
Recently, Low Earth Orbit (LEO) satellite Internet has been deployed and provides access
service. In the near future, with high-speed development and dense deployment of non …
service. In the near future, with high-speed development and dense deployment of non …