activity
20232026
most citedReinforcement Learning With LLMs Interaction For Distributed Diffusion Model Services

13 citations · 18 across the 7 of their papers we have counts for

collaborators

7 papers

cs.NI2026

Morphe: High-Fidelity Generative Video Streaming with Vision Foundation Model

Tianyi Gong, Zijian Cao, Zixing Zhang +4

Video streaming is a fundamental Internet service, while the quality still cannot be guaranteed especially in poor network conditions such as bandwidth-constrained and remote areas…

cs.IT2024

WDMoE: Wireless Distributed Large Language Models with Mixture of Experts

Nan Xue, Yaping Sun, Zhiyong Chen +5

Large Language Models (LLMs) have achieved significant success in various natural language processing tasks, but how wireless communications can support LLMs has not been extensive…

cs.LG2024

Scalable Federated Unlearning via Isolated and Coded Sharding

Yijing Lin, Zhipeng Gao, Hongyang Du +4

Federated unlearning has emerged as a promising paradigm to erase the client-level data effect without affecting the performance of collaborative learning models. However, the fede…

cs.NI2023★ 4 cited

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…

cs.NI2023★ 13 cited

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…

eess.SP2023★ 1 cited

Generative AI for Integrated Sensing and Communication: Insights from the Physical Layer Perspective

Jiacheng Wang, Hongyang Du, Dusit Niyato +4

As generative artificial intelligence (GAI) models continue to evolve, their generative capabilities are increasingly enhanced and being used extensively in content generation. Bey…

cs.NI2023

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…