activity
20242026
most citedNetLLM: Adapting Large Language Models for Networking

161 citations · 165 across the 3 of their papers we have counts for

collaborators

5 papers

cs.IT2026

Logit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networks

Lyutianyang Zhang, Yunjian Jia, Liu Cao +3

Distributed mixture-of-experts (MoE) inference is a promising architecture for deploying large language models (LLMs) at wireless edge networks because sparse experts can be placed…

eess.SP2025

Movable-Antenna Empowered AAV-Enabled Data Collection over Low-Altitude Wireless Networks

Xuhui Zhang, Wenchao Liu, Jinke Ren +4

Movable-antennas (MAs) are revolutionizing spatial signal processing by providing flexible beamforming in next-generation wireless systems. This paper investigates an MA-empowered…

cs.IT2024★ 3 cited

Generative Semantic Communication for Joint Image Transmission and Segmentation

Weiwen Yuan, Jinke Ren, Chongjie Wang +4

Semantic communication has emerged as a promising technology for enhancing communication efficiency. However, most existing research emphasizes single-task reconstruction, neglecti…

cs.SD2024★ 1 cited

Generative Semantic Communication for Text-to-Speech Synthesis

Jiahao Zheng, Jinke Ren, Peng Xu +5

Semantic communication is a promising technology to improve communication efficiency by transmitting only the semantic information of the source data. However, traditional semantic…

cs.NI2024★ 161 cited

NetLLM: Adapting Large Language Models for Networking

Duo Wu, Xianda Wang, Yaqi Qiao +4

Many networking tasks now employ deep learning (DL) to solve complex prediction and optimization problems. However, current design philosophy of DL-based algorithms entails intensi…