19 citations · 63 across the 15 of their papers we have counts for
5 papers · 1 filter
Hierarchical Debate-Based Large Language Model (LLM) for Complex Task Planning of 6G Network Management
Yuyan Lin, Hao Zhou, Chengming Hu +5
6G networks have become increasingly complicated due to novel network architecture and newly emerging signal processing and transmission techniques, leading to significant burdens…
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…