most citedToward Agentic AI: Generative Information Retrieval Inspired Intelligent Communications and Networking

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NI20252 cited

Toward Agentic AI: Generative Information Retrieval Inspired Intelligent Communications and Networking

Ruichen Zhang, Shunpu Tang, Yinqiu Liu +5

The increasing complexity and scale of modern telecommunications networks demand intelligent automation to enhance efficiency, adaptability, and resilience. Agentic AI has emerged…

cs.NI2025

Intelligent Mobile AI-Generated Content Services via Interactive Prompt Engineering and Dynamic Service Provisioning

Yinqiu Liu, Ruichen Zhang, Jiacheng Wang +4

Due to massive computational demands of large generative models, AI-Generated Content (AIGC) can organize collaborative Mobile AIGC Service Providers (MASPs) at network edges to pr…

cs.NI2025

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…

cs.NI20241 cited

Generative AI in Data Center Networking: Fundamentals, Perspectives, and Case Study

Yinqiu Liu, Hongyang Du, Dusit Niyato +4

Generative AI (GenAI), exemplified by Large Language Models (LLMs) such as OpenAI's ChatGPT, is revolutionizing various fields. Central to this transformation is Data Center Networ…

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…