136 citations · 196 across the 33 of their papers we have counts for
19 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…
Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
Ruichen Zhang, Guangyuan Liu, Yinqiu Liu +10
The rapid expansion of sixth-generation (6G) wireless networks and the Internet of Things (IoT) has catalyzed the evolution from centralized cloud intelligence towards decentralize…
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…
Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks
Minrui Xu, Jiani Fan, Xinyu Huang +8
With the continuous evolution of Large Language Models (LLMs), LLM-based agents have advanced beyond passive chatbots to become autonomous cyber entities capable of performing comp…
Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing
Minrui Xu, Dusit Niyato, Jiawen Kang +5
Exploiting quantum computing at the mobile edge holds immense potential for facilitating large-scale network design, processing multimodal data, optimizing resource management, and…
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…
Embodied AI-Enhanced Vehicular Networks: An Integrated Large Language Models and Reinforcement Learning Method
Ruichen Zhang, Changyuan Zhao, Hongyang Du +5
This paper investigates adaptive transmission strategies in embodied AI-enhanced vehicular networks by integrating large language models (LLMs) for semantic information extraction…
Toward Mixture-of-Experts Enabled Trustworthy Semantic Communication for 6G Networks
Jiayi He, Xiaofeng Luo, Jiawen Kang +5
Semantic Communication (SemCom) plays a pivotal role in 6G networks, offering a viable solution for future efficient communication. Deep Learning (DL)-based semantic codecs further…
Hierarchical Micro-Segmentations for Zero-Trust Services via Large Language Model (LLM)-enhanced Graph Diffusion
Yinqiu Liu, Guangyuan Liu, Hongyang Du +5
In the rapidly evolving Next-Generation Networking (NGN) era, the adoption of zero-trust architectures has become increasingly crucial to protect security. However, provisioning ze…
Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey
Minrui Xu, Dusit Niyato, Jiawen Kang +6
Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets, com…
Cross-Modal Generative Semantic Communications for Mobile AIGC: Joint Semantic Encoding and Prompt Engineering
Yinqiu Liu, Hongyang Du, Dusit Niyato +5
Employing massive Mobile AI-Generated Content (AIGC) Service Providers (MASPs) with powerful models, high-quality AIGC services can become accessible for resource-constrained end u…
ProSecutor: Protecting Mobile AIGC Services on Two-Layer Blockchain via Reputation and Contract Theoretic Approaches
Yinqiu Liu, Hongyang Du, Dusit Niyato +5
Mobile AI-Generated Content (AIGC) has achieved great attention in unleashing the power of generative AI and scaling the AIGC services. By employing numerous Mobile AIGC Service Pr…
Streamlined Transmission: A Semantic-Aware XR Deployment Framework Enhanced by Generative AI
Wanting Yang, Zehui Xiong, Tony Q. S. Quek +1
In the era of 6G, featuring compelling visions of digital twins and metaverses, Extended Reality (XR) has emerged as a vital conduit connecting the digital and physical realms, gar…
Dynamic Human Digital Twin Deployment at the Edge for Task Execution: A Two-Timescale Accuracy-Aware Online Optimization
Yuye Yang, You Shi, Changyan Yi +5
Human digital twin (HDT) is an emerging paradigm that bridges physical twins (PTs) with powerful virtual twins (VTs) for assisting complex task executions in human-centric services…
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,…
The Age of Generative AI and AI-Generated Everything
Hongyang Du, Dusit Niyato, Jiawen Kang +9
Generative AI (GAI) has emerged as a significant advancement in artificial intelligence, renowned for its language and image generation capabilities. This paper presents ``AI-Gener…
Reinforcement Learning With LLMs Interaction For Distributed Diffusion Model Services
Hongyang Du, Ruichen Zhang, Dusit Niyato +5
Distributed Artificial Intelligence-Generated Content (AIGC) has attracted significant attention, but two key challenges remain: maximizing subjective Quality of Experience (QoE) a…
Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Study
Ruichen Zhang, Ke Xiong, Hongyang Du +4
Recognizing the tremendous improvements that the integration of generative AI can bring to intelligent transportation systems, this article explores the integration of generative A…