219 citations · 378 across the 62 of their papers we have counts for
65 papers
Frequency-Aware Continual Learning for Smart Contract Vulnerability Detection with Large Language Models
Tenghui Huang, Jiawen Kang, Dongning Liu +5
Smart contract vulnerability detection with Large Language Models (LLMs) faces three causally linked challenges. First, new vulnerability categories demand parameter-efficient adap…
Split and Aggregation Learning for Foundation Models Over Mobile Embodied AI Network (MEAN): A Comprehensive Survey
Qianzhou Chen, Siqi Sun, Minrui Xu +6
The rapid advancements in foundation models and sixth-generation (6G) wireless communication systems necessitate the development of efficient, scalable, and privacy-preserving mach…
From Digital Twins to World Models:Opportunities, Challenges, and Applications for Mobile Edge General Intelligence
Jie Zheng, Dusit Niyato, Changyuan Zhao +2
The rapid evolution toward 6G and beyond communication systems is accelerating the convergence of digital twins and world models at the network edge. Traditional digital twins prov…
Agentic Cognitive Profiling: Realigning Automated Alzheimer's Disease Detection with Clinical Construct Validity
Jiawen Kang, Kun Li, Dongrui Han +5
Automated Alzheimer's Disease (AD) screening has predominantly followed the inductive paradigm of pattern recognition, which directly maps the input signal to the outcome label. Th…
Efficient Cross-View Localization in 6G Space-Air-Ground Integrated Network
Min Hao, Yanbing Xu, Maoqiang Wu +6
Recently, visual localization has become an important supplement to improve localization reliability, and cross-view approaches can greatly enhance coverage and adaptability. Meanw…
Compact LLM Deployment and World Model Assisted Offloading in Mobile Edge Computing
Ruichen Zhang, Xiaofeng Luo, Jiayi He +3
This paper investigates compact large language model (LLM) deployment and world-model-assisted inference offloading in mobile edge computing (MEC) networks. We first propose an edg…
Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization
Jie Zheng, Ruichen Zhang, Dusit Niyato +5
Enhancing future wireless networks presents a significant challenge for networking systems due to diverse user demands and the emergence of 6G technology. While reinforcement learn…
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…
Efficient Asynchronous Federated Evaluation with Strategy Similarity Awareness for Intent-Based Networking in Industrial Internet of Things
Shaowen Qin, Jianfeng Zeng, Haodong Guo +3
Intent-Based Networking (IBN) offers a promising paradigm for intelligent and automated network control in Industrial Internet of Things (IIoT) environments by translating high-lev…
Hybrid Stackelberg Game and Diffusion-based Auction for Two-tier Agentic AI Task Offloading in Internet of Agents
Yue Zhong, Yongju Tong, Jiawen Kang +4
The Internet of Agents (IoA) is rapidly gaining prominence as a foundational architecture for interconnected intelligent systems, designed to facilitate seamless discovery, communi…
DWM-RO: Decentralized World Models with Reasoning Offloading for SWIPT-enabled Satellite-Terrestrial HetNets
Guangyuan Liu, Yinqiu Liu, Ruichen Zhang +5
Wireless networks are undergoing a paradigm shift toward massive connectivity with energy-efficient operation, driving the integration of satellite-terrestrial architectures with s…
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…
Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges
Changyuan Zhao, Guangyuan Liu, Ruichen Zhang +11
Edge General Intelligence (EGI) represents a transformative evolution of edge computing, where distributed agents possess the capability to perceive, reason, and act autonomously a…
Context-Aware Semantic Communication for the Wireless Networks
Guangyuan Liu, Yinqiu Liu, Jiacheng Wang +5
In next-generation wireless networks, supporting real-time applications such as augmented reality, autonomous driving, and immersive Metaverse services demands stringent constraint…
Large Language Model-enhanced Reinforcement Learning for Low-Altitude Economy Networking
Lingyi Cai, Ruichen Zhang, Changyuan Zhao +5
Low-Altitude Economic Networking (LAENet) aims to support diverse flying applications below 1,000 meters by deploying various aerial vehicles for flexible and cost-effective aerial…
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…
Efficient Twin Migration in Vehicular Metaverses: Multi-Agent Split Deep Reinforcement Learning with Spatio-Temporal Trajectory Generation
Junlong Chen, Jiawen Kang, Minrui Xu +5
Vehicle Twins (VTs) as digital representations of vehicles can provide users with immersive experiences in vehicular metaverse applications, e.g., Augmented Reality (AR) navigation…
Federated Digital Twin Construction via Distributed Sensing: A Game-Theoretic Online Optimization with Overlapping Coalitions
Ruoyang Chen, Changyan Yi, Fuhui Zhou +3
In this paper, we propose a novel federated framework for constructing the digital twin (DT) model, referring to a living and self-evolving visualization model empowered by artific…
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…
Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks
Jiacheng Wang, Changyuan Zhao, Hongyang Du +5
Integrated sensing and communication (ISAC) uses the same software and hardware resources to achieve both communication and sensing functionalities. Thus, it stands as one of the c…
Achieving Network Resilience through Graph Neural Network-enabled Deep Reinforcement Learning
Xuzeng Li, Tao Zhang, Jian Wang +5
Deep reinforcement learning (DRL) has been widely used in many important tasks of communication networks. In order to improve the perception ability of DRL on the network, some stu…
Generative AI-driven Cross-layer Covert Communication: Fundamentals, Framework and Case Study
Tianhao Liu, Jiqiang Liu, Tao Zhang +5
Ensuring end-to-end cross-layer communication security in military networks by selecting covert schemes between nodes is a key solution for military communication security. With th…
Adaptive Contextual Caching for Mobile Edge Large Language Model Service
Guangyuan Liu, Yinqiu Liu, Jiacheng Wang +4
Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation…