Analysis of Privacy Leakage in Federated Large Language Models

arXiv:2403.04784v1 Announce Type: new
Abstract: With the rapid adoption of Federated Learning (FL) as the training and tuning protocol for applications utilizing Large Language Models (LLMs), recent research highlights the need for significant modifications to FL to accommodate the large-scale of LLMs. While substantial adjustments to the protocol have been introduced as a response, comprehensive privacy analysis for the adapted FL protocol is currently lacking.
To address this gap, our work delves into an extensive examination of the privacy analysis …

adoption analysis applications arxiv cs.cr cs.lg federated federated learning language language models large llms modifications privacy protocol rapid research scale training