5 citations · 18 across the 16 of their papers we have counts for
5 papers · 1 filter
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…
Visual Language Model based Cross-modal Semantic Communication Systems
Feibo Jiang, Chuanguo Tang, Li Dong +3
Semantic Communication (SC) has emerged as a novel communication paradigm in recent years, successfully transcending the Shannon physical capacity limits through innovative semanti…
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…
Large Generative Model Assisted 3D Semantic Communication
Feibo Jiang, Yubo Peng, Li Dong +4
Semantic Communication (SC) is a novel paradigm for data transmission in 6G. However, there are several challenges posed when performing SC in 3D scenarios: 1) 3D semantic extracti…