3 citations · 8 across the 7 of their papers we have counts for
8 papers
Decoding RWA Tokenized U.S. Treasuries: Functional Dissection and Address Role Inference
Junliang Luo, Katrin Tinn, Samuel Ferreira Duran +2
Tokenized U.S. Treasuries have emerged as a prominent subclass of real-world assets (RWAs), offering cryptographically secured, yield-bearing instruments issued across multi-chain…
Prompting Wireless Networks: Reinforced In-Context Learning for Power Control
Hao Zhou, Chengming Hu, Dun Yuan +5
To manage and optimize constantly evolving wireless networks, existing machine learning (ML)- based studies operate as black-box models, leading to increased computational costs du…
Enhancing Large Language Models (LLMs) for Telecommunications using Knowledge Graphs and Retrieval-Augmented Generation
Dun Yuan, Hao Zhou, Di Wu +5
Large language models (LLMs) have made significant progress in general-purpose natural language processing tasks. However, LLMs are still facing challenges when applied to domain-s…
Large Language Models for Wireless Networks: An Overview from the Prompt Engineering Perspective
Hao Zhou, Chengming Hu, Dun Yuan +5
Recently, large language models (LLMs) have been successfully applied to many fields, showing outstanding comprehension and reasoning capabilities. Despite their great potential, L…
Self-Refined Generative Foundation Models for Wireless Traffic Prediction
Chengming Hu, Hao Zhou, Di Wu +3
With a broad range of emerging applications in 6G networks, wireless traffic prediction has become a critical component of network management. However, the dynamically shifting dis…
Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-context Learning
Hao Zhou, Chengming Hu, Dun Yuan +5
Generative artificial intelligence (GAI) is a promising technique towards 6G networks, and generative foundation models such as large language models (LLMs) have attracted consider…
Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control
Hao Zhou, Chengming Hu, Dun Yuan +4
Large language model (LLM) has recently been considered a promising technique for many fields. This work explores LLM-based wireless network optimization via in-context learning. T…
Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities
Hao Zhou, Chengming Hu, Ye Yuan +11
Large language models (LLMs) have received considerable attention recently due to their outstanding comprehension and reasoning capabilities, leading to great progress in many fiel…