activity
20232026
most citedInteractive AI with Retrieval-Augmented Generation for Next Generation Networking

136 citations · 196 across the 33 of their papers we have counts for

collaborators
Showing 2024Show all

14 papers · 1 filter

cs.NI2024

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…

eess.SP2024★ 2 cited

Generative AI based Secure Wireless Sensing for ISAC Networks

Jiacheng Wang, Hongyang Du, Yinqiu Liu +5

Integrated sensing and communications (ISAC) is expected to be a key technology for 6G, and channel state information (CSI) based sensing is a key component of ISAC. However, curre…

cs.NI2024★ 2 cited

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…

cs.CR2024

Enhancing Physical Layer Communication Security through Generative AI with Mixture of Experts

Changyuan Zhao, Hongyang Du, Dusit Niyato +6

AI technologies have become more widely adopted in wireless communications. As an emerging type of AI technologies, the generative artificial intelligence (GAI) gains lots of atten…

cs.IT2024

AoI-aware Sensing Scheduling and Trajectory Optimization for Multi-UAV-assisted Wireless Backscatter Networks

Yusi Long, Songhan Zhao, Shimin Gong +4

This paper considers multiple unmanned aerial vehicles (UAVs) to assist sensing data transmissions from the ground users (GUs) to a remote base station (BS). Each UAV collects sens…

cs.NI2024★ 4 cited

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…

cs.NI2024

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…

cs.NI2024

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…

cs.NI2024

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…

cs.IT2024★ 1 cited

Graph Neural Network Meets Multi-Agent Reinforcement Learning: Fundamentals, Applications, and Future Directions

Ziheng Liu, Jiayi Zhang, Enyu Shi +5

Multi-agent reinforcement learning (MARL) has become a fundamental component of next-generation wireless communication systems. Theoretically, although MARL has the advantages of l…

cs.CR2024★ 4 cited

Generative AI for Secure Physical Layer Communications: A Survey

Changyuan Zhao, Hongyang Du, Dusit Niyato +6

Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating rapid advancement and unparalleled proficiency in generating diverse content. Beyon…

eess.SP2024

Collaborative Computing in Non-Terrestrial Networks: A Multi-Time-Scale Deep Reinforcement Learning Approach

Yang Cao, Shao-Yu Lien, Ying-Chang Liang +3

Constructing earth-fixed cells with low-earth orbit (LEO) satellites in non-terrestrial networks (NTNs) has been the most promising paradigm to enable global coverage. The limited…

cs.NI2024★ 1 cited

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…

cs.NI2024★ 136 cited

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,…