5 papers
Delay-Aware Large-Small Model Collaboration over LEO Satellite Networks
Mingyu Guo, Wen Wu, Ying Wang +2
In this paper, we introduce a delay-aware largesmall model collaboration scheme for low Earth orbit (LEO) satellite networks, which can balance the computational load among satelli…
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…
SplitLLM: Hierarchical Split Learning for Large Language Model over Wireless Network
Songge Zhang, Guoliang Cheng, Zuguang Li +1
Fine-tuning a large language model (LLM) using the local data of edge users can enable personalized services and applications. For privacy protection, the prevalent solution adopts…
Split Fine-Tuning for Large Language Models in Wireless Networks
Songge Zhang, Guoliang Cheng, Xinyu Huang +4
Fine-tuning is the process of adapting the pre-trained large language models (LLMs) for downstream tasks. Due to substantial parameters, fine-tuning LLMs on mobile devices demands…
Energy-Efficient Split Learning for Fine-Tuning Large Language Models in Edge Networks
Zuguang Li, Shaohua Wu, Liang Li +1
In this letter, we propose an energy-efficient split learning (SL) framework for fine-tuning large language models (LLMs) using geo-distributed personal data at the network edge, w…