5 papers
Tutorial on Large Language Model-Enhanced Reinforcement Learning for Wireless Networks
Lingyi Cai, Wenjie Fu, Yuxi Huang +9
Reinforcement Learning (RL) has shown remarkable success in enabling adaptive and data-driven optimization for various applications in wireless networks. However, classical RL suff…
LAMeTA: Intent-Aware Agentic Network Optimization via a Large AI Model-Empowered Two-Stage Approach
Yinqiu Liu, Guangyuan Liu, Jiacheng Wang +5
Nowadays, Generative AI (GenAI) reshapes numerous domains by enabling machines to create content across modalities. As GenAI evolves into autonomous agents capable of reasoning, co…
ContribChain: A Stress-Balanced Blockchain Sharding Protocol with Node Contribution Awareness
Xinpeng Huang, Wanqing Jie, Shiwen Zhang +8
Existing blockchain sharding protocols have focused on eliminating imbalanced workload distributions. However, even with workload balance, disparities in processing capabilities ca…
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…
Wireless Hallucination in Generative AI-enabled Communications: Concepts, Issues, and Solutions
Xudong Wang, Jiacheng Wang, Lei Feng +6
Generative AI (GenAI) is driving the intelligence of wireless communications. Due to data limitations, random generation, and dynamic environments, GenAI may generate channel infor…