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 achieves superior results in machine translation tasks while being more parallelizable and requiring significantly less time to train. The core idea is using self-attention to relate different positions of the input sequence to compute a representation of the entire sequence.