Attention is All You Need

This paper introduces the Transformer, a novel neural network architecture based solely on attention mechanisms. Unlike previous models that relied on recurrent or convolutional layers, the Transformer uses self-attention to weigh the importance of different parts of the input sequence, allowing for parallelization and significantly improved performance on various natural language processing tasks. It has become a foundational model for many subsequent advancements in the field.