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 to weigh the importance of different parts of the input sequence when processing it, allowing for parallelization and capturing long-range dependencies more effectively than recurrent models.