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 architecture can be trained faster and achieve state-of-the-art results in machine translation tasks. The Transformer model's parallelizable nature and reliance on attention make it highly efficient and effective for processing sequential data.