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 model can be trained faster and achieves state-of-the-art results in machine translation tasks. The core idea is using self-attention to relate different positions of a single sequence in order to compute a representation of the sequence.