709 citations · 2.7k across the 86 of their papers we have counts for
28 papers · 1 filter
Large Language Models for Networking: Applications, Enabling Techniques, and Challenges
Yudong Huang, Hongyang Du, Xinyuan Zhang +5
The rapid evolution of network technologies and the growing complexity of network tasks necessitate a paradigm shift in how networks are designed, configured, and managed. With a w…
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…
A Unified Framework for Guiding Generative AI with Wireless Perception in Resource Constrained Mobile Edge Networks
Jiacheng Wang, Hongyang Du, Dusit Niyato +6
With the significant advancements in artificial intelligence (AI) technologies and powerful computational capabilities, generative AI (GAI) has become a pivotal digital content gen…
Optimizing Mobile-Edge AI-Generated Everything (AIGX) Services by Prompt Engineering: Fundamental, Framework, and Case Study
Yinqiu Liu, Hongyang Du, Dusit Niyato +4
As the next-generation paradigm for content creation, AI-Generated Content (AIGC), i.e., generating content automatically by Generative AI (GAI) based on user prompts, has gained g…
Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization
Hongyang Du, Ruichen Zhang, Yinqiu Liu +10
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy a…
Semantic Communications for Artificial Intelligence Generated Content (AIGC) Toward Effective Content Creation
Guangyuan Liu, Hongyang Du, Dusit Niyato +5
Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation base…
A Revolution of Personalized Healthcare: Enabling Human Digital Twin with Mobile AIGC
Jiayuan Chen, Changyan Yi, Hongyang Du +5
Mobile Artificial Intelligence-Generated Content (AIGC) technology refers to the adoption of AI algorithms deployed at mobile edge networks to automate the information creation pro…
Joint Foundation Model Caching and Inference of Generative AI Services for Edge Intelligence
Minrui Xu, Dusit Niyato, Hongliang Zhang +4
With the rapid development of artificial general intelligence (AGI), various multimedia services based on pretrained foundation models (PFMs) need to be effectively deployed. With…
Sparks of GPTs in Edge Intelligence for Metaverse: Caching and Inference for Mobile AIGC Services
Minrui Xu, Dusit Niyato, Hongliang Zhang +4
Aiming at achieving artificial general intelligence (AGI) for Metaverse, pretrained foundation models (PFMs), e.g., generative pretrained transformers (GPTs), can effectively provi…
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…
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…
Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study
Yinqiu Liu, Hongyang Du, Dusit Niyato +4
With the phenomenal success of diffusion models and ChatGPT, deep generation models (DGMs) have been experiencing explosive growth from 2022. Not limited to content generation, DGM…
Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services
Minrui Xu, Hongyang Du, Dusit Niyato +9
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This s…
Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services
Hongyang Du, Zonghang Li, Dusit Niyato +4
As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AIGenerated Content (AIGC) emerges as a key solution, yet t…
A Blockchain-based Semantic Exchange Framework for Web 3.0 toward Participatory Economy
Yijing Lin, Zhipeng Gao, Yaofeng Tu +4
Web 3.0 is the next-generation Internet that enables participants to read, write, and own contents in a decentralized manner. It is mainly driven by blockchain, semantic communicat…
EPViSA: Efficient Auction Design for Real-time Physical-Virtual Synchronization in the Metaverse
Minrui Xu, Dusit Niyato, Benjamin Wright +5
Metaverse can obscure the boundary between the physical and virtual worlds. Specifically, for the Metaverse in vehicular networks, i.e., the vehicular Metaverse, vehicles are no lo…
Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing
Minrui Xu, Dusit Niyato, Jiawen Kang +2
In this paper, a novel paradigm of mobile edge-quantum computing (MEQC) is proposed, which brings quantum computing capacities to mobile edge networks that are closer to mobile use…
Rethinking Wireless Communication Security in Semantic Internet of Things
Hongyang Du, Jiacheng Wang, Dusit Niyato +4
Semantic communication is an important participant in the next generation of wireless communications. Enabled by this novel paradigm, the conventional Internet-of-Things (IoT) is e…
Privacy-preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet
Minrui Xu, Dusit Niyato, Zhaohui Yang +5
Federated edge learning (FEL) is a promising paradigm of distributed machine learning that can preserve data privacy while training the global model collaboratively. However, FEL i…
Slicing4Meta: An Intelligent Integration Framework with Multi-dimensional Network Resources for Metaverse-as-a-Service in Web 3.0
Yi-Jing Liu, Hongyang Du, Dusit Niyato +3
As the next-generation Internet paradigm, Web 3.0 encapsulates the expectations of user-centric immersion and interaction experiences in a decentralized manner. Metaverse, a virtua…
Rethinking Quality of Experience for Metaverse Services: A Consumer-based Economics Perspective
Hongyang Du, Bohao Ma, Dusit Niyato +3
The Metaverse is considered to be one prototype of the next-generation Internet, which contains people's expectations for the future world. However, the academic discussion of the…
Exploring Attention-Aware Network Resource Allocation for Customized Metaverse Services
Hongyang Du, Jiacheng Wang, Dusit Niyato +5
Emerging with the support of computing and communications technologies, Metaverse is expected to bring users unprecedented service experiences. However, the increase in the number…
6G-enabled Edge AI for Metaverse: Challenges, Methods, and Future Research Directions
Luyi Chang, Zhe Zhang, Pei Li +8
6G-enabled edge intelligence opens up a new era of Internet of Everything and makes it possible to interconnect people-devices-cloud anytime, anywhere. More and more next-generatio…