9 papers
NetMCP: Network-Aware Model Context Protocol Platform for LLM Capability Extension
Enhan Li, Hongyang Du, Kaibin Huang
Large Language Models (LLMs) remain static in functionality after training, and extending their capabilities requires integration with external data, computation, and services. The…
Experience Scaling: Post-Deployment Evolution For Large Language Models
Xingkun Yin, Kaibin Huang, Dong In Kim +1
Scaling model size, training data, and compute power have driven advances in large language models (LLMs), but these approaches are reaching saturation as human-generated text is e…
Ubiquitous Intelligence Via Wireless Network-Driven LLMs Evolution
Xingkun Yin, Feiran You, Hongyang Du +1
We introduce ubiquitous intelligence as a paradigm where Large Language Models (LLMs) evolve within wireless network-driven ecosystems. Unlike static model deployments, this approa…
LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction
Shiyuan Zhang, Tong Li, Zhu Xiao +2
Service-level mobile traffic prediction for individual users is essential for network efficiency and quality of service enhancement. However, current prediction methods are limited…
Energy-Efficient RSMA-enabled Low-altitude MEC Optimization Via Generative AI-enhanced Deep Reinforcement Learning
Xudong Wang, Hongyang Du, Lei Feng +1
The growing demand for low-latency computing in 6G is driving the use of UAV-based low-altitude mobile edge computing (MEC) systems. However, limited spectrum often leads to severe…
DRESS: Diffusion Reasoning-based Reward Shaping Scheme For Intelligent Networks
Feiran You, Hongyang Du, Xiangwang Hou +2
Network optimization remains fundamental in wireless communications, with Artificial Intelligence (AI)-based solutions gaining widespread adoption. As Sixth-Generation (6G) communi…