3 papers
eess.SY2025
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…
cs.LG2025
Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?
Xi Chen, Kaituo Feng, Changsheng Li +4
Low-rank training has emerged as a promising approach for reducing memory usage in training Large Language Models (LLMs). Previous methods either rely on decomposing weight matrice…
cs.NI2024
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…