Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services

M Xu, H Du, D Niyato, J Kang, Z Xiong… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

Efficient parallel split learning over resource-constrained wireless edge networks

Z Lin, G Zhu, Y Deng, X Chen, Y Gao… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The increasingly deeper neural networks hinder the democratization of privacy-enhancing
distributed learning, such as federated learning (FL), to resource-constrained devices. To …

Split learning in 6g edge networks

Z Lin, G Qu, X Chen, K Huang - IEEE Wireless …, 2024 - ieeexplore.ieee.org
With the proliferation of distributed edge computing resources, the 6G mobile network will
evolve into a network for connected intelligence. Along this line, the proposal to incorporate …

Large language model (llm) for telecommunications: A comprehensive survey on principles, key techniques, and opportunities

H Zhou, C Hu, Y Yuan, Y Cui, Y Jin, C Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) have received considerable attention recently due to their
outstanding comprehension and reasoning capabilities, leading to great progress in many …

Fedsn: A general federated learning framework over leo satellite networks

Z Lin, Z Chen, Z Fang, X Chen, X Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

Adaptsfl: Adaptive split federated learning in resource-constrained edge networks

Z Lin, G Qu, W Wei, X Chen, KK Leung - arXiv preprint arXiv:2403.13101, 2024 - arxiv.org
The increasing complexity of deep neural networks poses significant barriers to
democratizing them to resource-limited edge devices. To address this challenge, split …

Automated federated pipeline for parameter-efficient fine-tuning of large language models

Z Fang, Z Lin, Z Chen, X Chen, Y Gao… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, there has been a surge in the development of advanced intelligent generative
content (AIGC), especially large language models (LLMs). However, for many downstream …

AI-native interconnect framework for integration of large language model technologies in 6G systems

S Tarkoma, R Morabito, J Sauvola - arXiv preprint arXiv:2311.05842, 2023 - arxiv.org
The evolution towards 6G architecture promises a transformative shift in communication
networks, with artificial intelligence (AI) playing a pivotal role. This paper delves deep into …

When large language model agents meet 6G networks: Perception, grounding, and alignment

M Xu, N Dusit, J Kang, Z Xiong, S Mao, Z Han… - arXiv preprint arXiv …, 2024 - arxiv.org
AI agents based on multimodal large language models (LLMs) are expected to revolutionize
human-computer interaction and offer more personalized assistant services across various …

Leveraging large language models for intelligent control of 6g integrated tn-ntn with iot service

B Rong, H Rutagemwa - IEEE Network, 2024 - ieeexplore.ieee.org
With the advent of sixth generation (6G) Internet of Things (IoT), integrated terrestrial network
(TN) and non-terrestrial network (NTN) will play a vital role in enabling new applications and …