Abstract: Split Federated Learning (SFL) improves scalability of Split Learning (SL) by enabling parallel computing of the learning tasks on multiple clients. However, state-of-the-art SFL schemes ...

Abstract: Resource-constrained organizations with vast datasets often face significant challenges in training and fine-tuning large language models (LLMs) due to privacy and compliance requirements.