2 citations · 2 across the 6 of their papers we have counts for
6 papers
CORE:Toward Ubiquitous 6G Intelligence Through Collaborative Orchestration of Large Language Model Agents Over Hierarchical Edge
Zitong Yu, Boquan Sun, Yang Li +2
Rapid advancements in sixth-generation (6G) networks and large language models (LLMs) have paved the way for ubiquitous intelligence, wherein seamless connectivity and distributed…
LLM Enabled Multi-Agent System for 6G Networks: Framework and Method of Dual-Loop Edge-Terminal Collaboration
Zheyan Qu, Wenbo Wang, Zitong Yu +3
The ubiquitous computing resources in 6G networks provide ideal environments for the fusion of large language models (LLMs) and intelligent services through the agent framework. Wi…
Incentive-Driven Task Offloading and Collaborative Computing in Device-Assisted MEC Networks
Yang Li, Xing Zhang, Bo Lei +4
Edge computing (EC), positioned near end devices, holds significant potential for delivering low-latency, energy-efficient, and secure services. This makes it a crucial component o…
Priority and Stackelberg Game-Based Incentive Task Allocation for Device-Assisted MEC Networks
Yang Li, Xing Zhang, Bo Lei +2
Mobile edge computing (MEC) is a promising computing paradigm that offers users proximity and instant computing services for various applications, and it has become an essential co…
CourseGPT-zh: an Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimization
Zheyan Qu, Lu Yin, Zitong Yu +2
Large language models (LLMs) have demonstrated astonishing capabilities in natural language processing (NLP) tasks, sparking interest in their application to professional domains w…
Computation Rate Maximization for Wireless Powered Edge Computing With Multi-User Cooperation
Yang Li, Xing Zhang, Bo Lei +4
The combination of mobile edge computing (MEC) and radio frequency-based wireless power transfer (WPT) presents a promising technique for providing sustainable energy supply and co…