5 papers
Broadcast Rate Limits in Wi-Fi: A Forgotten Bottleneck for Collaborative Edge LLM Inference
Liujianfu Wang, Yuyang Du, Shiqi Xu +1
LLM deployment is migrating from data centers to edge devices, where Mixture-of-Experts (MoE) models offer a promising path: sparse expert activation allows the model to be spread…
LLMind 2.0: Distributed IoT Automation with Natural Language M2M Communication and Lightweight LLM Agents
Yuyang Du, Qun Yang, Liujianfu Wang +3
Recent advances in large language models (LLMs) have generated great interest in their applications for IoT automation and device management. However, centralized approaches strugg…
OD-MoE: On-Demand Expert Loading for Cacheless Edge-Distributed MoE Inference
Liujianfu Wang, Yuyang Du, Yuchen Pan +3
Mixture-of-Experts (MoE), while offering significant advantages as a Large Language Model (LLM) architecture, faces substantial challenges when deployed on low-cost edge devices wi…
Cellular-X: An LLM-empowered Cellular Agent for Efficient Base Station Operations
Liujianfu Wang, Xinyi Long, Yuyang Du +3
This paper introduces Cellular-X, an LLM-powered agent designed to automate cellular base station (BS) maintenance. Leveraging multimodal LLM and retrieval-augmented generation (RA…
Rephrase and Contrast: Fine-Tuning Language Models for Enhanced Understanding of Communication and Computer Networks
Liujianfu Wang, Yuyang Du, Jingqi Lin +2
Large language models (LLMs) are being widely researched across various disciplines, with significant recent efforts focusing on adapting LLMs for understanding of how communicatio…