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 architecture can be trained faster and achieves state-of-the-art results in machine translation tasks. The Transformer's reliance on attention allows for more parallelization during training and establishes new benchmarks for quality and efficiency.