Attention is all you need

This paper introduces the Transformer, a novel neural network architecture based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. It demonstrates that this new architecture achieves state-of-the-art results in machine translation tasks while being more parallelizable and requiring significantly less time to train. The attention mechanism allows the model to focus on different parts of the input sequence when producing each part of the output sequence, capturing long-range dependencies more effectively.