7 papers · 1 filter
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…
Enhancing Wireless Networks for IoT with Large Vision Models: Foundations and Applications
Yunting Xu, Jiacheng Wang, Ruichen Zhang +6
Large vision models (LVMs) have emerged as a foundational paradigm in visual intelligence, achieving state-of-the-art performance across diverse visual tasks. Recent advances in LV…
A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach for UAV-Assisted Vehicular Networks with Delayed CSI Feedback
Zhang Liu, Lianfen Huang, Zhibin Gao +4
Low altitude uncrewed aerial vehicles (UAVs) are expected to facilitate the development of aerial-ground integrated intelligent transportation systems and unlocking the potential o…
Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration
Haoxiang Luo, Yinqiu Liu, Ruichen Zhang +7
Edge computing enables real-time data processing closer to its source, thus improving the latency and performance of edge-enabled AI applications. However, traditional AI models of…
Intelligent Mobile AI-Generated Content Services via Interactive Prompt Engineering and Dynamic Service Provisioning
Yinqiu Liu, Ruichen Zhang, Jiacheng Wang +4
Due to massive computational demands of large generative models, AI-Generated Content (AIGC) can organize collaborative Mobile AIGC Service Providers (MASPs) at network edges to pr…
Generative AI for Lyapunov Optimization Theory in UAV-based Low-Altitude Economy Networking
Zhang Liu, Dusit Niyato, Jiacheng Wang +4
Lyapunov optimization theory has recently emerged as a powerful mathematical framework for solving complex stochastic optimization problems by transforming long-term objectives int…
Retrieval-augmented Generation for GenAI-enabled Semantic Communications
Shunpu Tang, Ruichen Zhang, Yuxuan Yan +4
Semantic communication (SemCom) is an emerging paradigm aiming at transmitting only task-relevant semantic information to the receiver, which can significantly improve communicatio…