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20232026
most citedEnhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

21 citations · 33 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.NI2025

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…

cs.NI2025★ 7 cited

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…

cs.NI2025★ 3 cited

Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences

Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132

This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…

cs.NI2024

Empowering Wireless Networks with Artificial Intelligence Generated Graph

Jiacheng Wang, Yinqiu Liu, Hongyang Du +4

In wireless communications, transforming network into graphs and processing them using deep learning models, such as Graph Neural Networks (GNNs), is one of the mainstream network…

cs.NI2024

Blockchain-based Pseudonym Management for Vehicle Twin Migrations in Vehicular Edge Metaverse

Jiawen Kang, Xiaofeng Luo, Jiangtian Nie +6

Driven by the great advances in metaverse and edge computing technologies, vehicular edge metaverses are expected to disrupt the current paradigm of intelligent transportation syst…

cs.NI2023★ 21 cited

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…