Federated Fine-Tuning of Large Language Models on Resource-Constrained Edge Devices: Opportunities, Challenges, and Tradeoffs

Federated learning offers a promising approach to fine-tune large language models on diverse, distributed data at the network edge, but faces significant computational, communication, and energy efficiency challenges that must be addressed.