5 papers · 1 filter
Personalized Wireless Federated Learning for Large Language Models
Feibo Jiang, Li Dong, Siwei Tu +5
Large language models (LLMs) have driven profound transformations in wireless networks. However, within wireless environments, the training of LLMs faces significant challenges rel…
SIMAC: A Semantic-Driven Integrated Multimodal Sensing And Communication Framework
Yubo Peng, Luping Xiang, Kun Yang +3
Traditional single-modality sensing faces limitations in accuracy and capability, and its decoupled implementation with communication systems increases latency in bandwidth-constra…
Explainable Semantic Federated Learning Enabled Industrial Edge Network for Fire Surveillance
Li Dong, Yubo Peng, Feibo Jiang +2
In fire surveillance, Industrial Internet of Things (IIoT) devices require transmitting large monitoring data frequently, which leads to huge consumption of spectrum resources. Hen…
GAI-Enabled Explainable Personalized Federated Semi-Supervised Learning
Yubo Peng, Feibo Jiang, Li Dong +2
Federated learning (FL) is a commonly distributed algorithm for mobile users (MUs) training artificial intelligence (AI) models, however, several challenges arise when applying FL…
Personalized Federated Learning for Generative AI-Assisted Semantic Communications
Yubo Peng, Feibo Jiang, Li Dong +2
Semantic Communication (SC) focuses on transmitting only the semantic information rather than the raw data. This approach offers an efficient solution to the issue of spectrum reso…