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 attention mechanisms alone can achieve state-of-the-art results in machine translation tasks, outperforming existing models that rely on recurrent or convolutional layers. The Transformer's parallelizable nature and reliance on attention make it more efficient and effective for processing sequential data.