2 citations · 3 across the 25 of their papers we have counts for
15 papers · 1 filter
JAUNT: Joint Alignment of User Intent and Network State for QoE-centric LLM Tool Routing
Enhan Li, Hongyang Du
Large Language Models (LLMs) increasingly rely on emerging protocols such as the Model Context Protocol (MCP) to invoke external tools and services. However, current tool routing m…
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…
Generative Feature Imputing -- A Technique for Error-resilient Semantic Communication
Jianhao Huang, Qunsong Zeng, Hongyang Du +1
Semantic communication (SemCom) has emerged as a promising paradigm for achieving unprecedented communication efficiency in sixth-generation (6G) networks by leveraging artificial…
User-Intent-Driven Semantic Communication via Adaptive Deep Understanding
Peigen Ye, Jingpu Duan, Hongyang Du +1
Semantic communication focuses on transmitting task-relevant semantic information, aiming for intent-oriented communication. While existing systems improve efficiency by extracting…
M3LLM: Model Context Protocol-aided Mixture of Vision Experts For Multimodal LLMs in Networks
Yongjie Zeng, Hongyang Du
Current Multimodal Large Language Models (MLLMs) rely on centralized architectures and often suffer from poor alignment between the input task and their fixed visual encoding modul…
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…
MAD-Spear: A Conformity-Driven Prompt Injection Attack on Multi-Agent Debate Systems
Yu Cui, Hongyang Du
Multi-agent debate (MAD) systems leverage collaborative interactions among large language models (LLMs) agents to improve reasoning capabilities. While recent studies have focused…
How to Design and Train Your Implicit Neural Representation for Video Compression
Matthew Gwilliam, Roy Zhang, Namitha Padmanabhan +2
Implicit neural representation (INR) methods for video compression have recently achieved visual quality and compression ratios that are competitive with traditional pipelines. How…
Empowering Intelligent Low-altitude Economy with Large AI Model Deployment
Zhonghao Lyu, Yulan Gao, Junting Chen +4
Low-altitude economy (LAE) represents an emerging economic paradigm that redefines commercial and social aerial activities. Large artificial intelligence models (LAIMs) offer trans…
ReaCritic: Reasoning Transformer-based DRL Critic-model Scaling For Wireless Networks
Feiran You, Hongyang Du
Heterogeneous Networks (HetNets) pose critical challenges for intelligent management due to the diverse user requirements and time-varying wireless conditions. These factors introd…
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…
Optimal Expert Selection for Distributed Mixture-of-Experts at the Wireless Edge
Shengling Qin, Hai Wu, Hongyang Du +1
The emergence of distributed Mixture-of-Experts (DMoE) systems, which deploy expert models at edge nodes, offers a pathway to achieving connected intelligence in sixth-generation (…
Generative AI-enabled Wireless Communications for Robust Low-Altitude Economy Networking
Changyuan Zhao, Jiacheng Wang, Ruichen Zhang +5
Low-Altitude Economy Networks (LAENets) have emerged as significant enablers of social activities, offering low-altitude services such as the transportation of packages, groceries,…