2 papers
cs.LG2025
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…
cs.LG2024
Split Knowledge Distillation for Large Models in IoT: Architecture, Challenges, and Solutions
Zuguang Li, Wen Wu, Shaohua Wu +3
Large models (LMs) have immense potential in Internet of Things (IoT) systems, enabling applications such as intelligent voice assistants, predictive maintenance, and healthcare mo…