Survey on federated learning for large language models published in Machine Learning

Our survey Federated Learning for Large Language Models: Opportunities, Challenges, and Open Research Directions, with Fatiha Ait Baali, Chaima Lhasnaoui and Tarik Agouti, is now published in Machine Learning (volume 115, issue 9, article 202).

The survey looks at how large language models can be trained and fine-tuned across organisations without pooling their data, the challenges that raises, and the research directions that remain open.

Read the article or see it in my publications.