Yang Yang

Federated Fine-Tuning of Large Language Models on Resource-Constrained Clients: Technical Approaches, Resource Costs, and Applicability

Federated fine-tuning adapts language models to distributed data and is widely adopted as a privacy-preserving alternative to centralized training, yet constrained clients must still store model weights and training states, execute updates, and communicate with a server. This review examines four composable routes---pa...