4 papers
Fast AI Model Partition for Split Learning over Edge Networks
Zuguang Li, Wen Wu, Shaohua Wu +2
Split learning (SL) is a distributed learning paradigm that can enable computation-intensive artificial intelligence (AI) applications by partitioning AI models between mobile devi…
Communication-Efficient Collaborative LLM Inference over LEO Satellite Networks
Songge Zhang, Wen Wu, Liang Li +3
Low Earth orbit (LEO) satellites play an essential role in intelligent Earth observation by leveraging artificial intelligence models. However, limited onboard memory and excessive…
MobiLLM: Enabling LLM Fine-Tuning on the Mobile Device via Server Assisted Side Tuning
Liang Li, Xingke Yang, Wen Wu +5
Large Language Model (LLM) at mobile devices and its potential applications never fail to fascinate. However, on-device LLM fine-tuning poses great challenges due to extremely high…
Edge-Assisted Accelerated Cooperative Sensing for CAVs: Task Placement and Resource Allocation
Yuxuan Wang, Kaige Qu, Wen Wu +2
In this paper, we propose a novel road side unit (RSU)-assisted cooperative sensing scheme for connected autonomous vehicles (CAVs), with the objective to reduce completion time of…