2024
Safely Learning with Private Data: A Federated Learning Framework for Large Language Model
EMNLP 2024main
Private data, being larger and quality-higher than public data, can greatly improve large language models (LLM). However, due to privacy concerns, this data is often dispersed in multiple silos, making its secure utilization for LLM training a challenge. Federated learning (FL) is an ideal solution…