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 state-of-the-art results in machine translation tasks. The core innovation lies in its ability to weigh the importance of different parts of the input sequence when processing it, leading to improved performance and parallelization capabilities.