328 citations
- Sun Yat-sen UniversityCN37 papers
- Nanyang Technological UniversitySG26 papers
- University of Hong KongHK25 papers
- Chinese University of Hong Kong, ShenzhenCN24 papers
- South China University of TechnologyCN24 papers
- National University of SingaporeSG22 papers
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- South China Agricultural UniversityCN18 papers
- Chinese Academy of SciencesCN17 papers
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- University of MacauMO12 papers
17 papers · 1 filter
Mixture of Experts for Decentralized Generative AI and Reinforcement Learning in Wireless Networks: A Comprehensive Survey
Yunting Xu, Jiacheng Wang, Ruichen Zhang +10
Mixture of Experts (MoE) has emerged as a promising paradigm for scaling model capacity while preserving computational efficiency, particularly in large-scale machine learning arch…
Digital Twin-Empowered Task Assignment in Aerial MEC Network: A Resource Coalition Cooperation Approach with Generative Model
Xin Tang, Qian Chen, Rong Yu +1
To meet the demands for ubiquitous communication and temporary edge computing in 6G networks, aerial mobile edge computing (MEC) networks have been envisioned as a new paradigm. Ho…
Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission
Ruichen Zhang, Hongyang Du, Yinqiu Liu +5
In response to the needs of 6G global communications, satellite communication networks have emerged as a key solution. However, the large-scale development of satellite communicati…
Interactive AI with Retrieval-Augmented Generation for Next Generation Networking
Ruichen Zhang, Hongyang Du, Yinqiu Liu +5
With the advance of artificial intelligence (AI), the emergence of Google Gemini and OpenAI Q* marks the direction towards artificial general intelligence (AGI). To implement AGI,…
Generative AI for Space-Air-Ground Integrated Networks
Ruichen Zhang, Hongyang Du, Dusit Niyato +5
Recently, generative AI technologies have emerged as a significant advancement in artificial intelligence field, renowned for their language and image generation capabilities. Mean…
FAST: Fidelity-Adjustable Semantic Transmission over Heterogeneous Wireless Networks
Peichun Li, Guoliang Cheng, Jiawen Kang +4
In this work, we investigate the challenging problem of on-demand semantic communication over heterogeneous wireless networks. We propose a fidelity-adjustable semantic transmissio…