What is FLT?

FLT most likely refers to Federated Learning of Transformers. Federated Learning (FL) is a machine learning technique that trains an algorithm across multiple decentralized edge devices or servers holding local data samples, without exchanging them. This contrasts with traditional centralized machine learning techniques where all the data is uploaded to a single server. Transformers are a type of neural network architecture that have achieved state-of-the-art results in many natural language processing tasks. Federated Learning of Transformers would involve training Transformer models using federated learning techniques, enabling collaborative model training without sharing the raw data.