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 achieve better results on machine translation tasks compared to previous models. The core innovation lies in the self-attention mechanism, which allows the model to weigh the importance of different parts of the input sequence when processing it.