Attention is All You Need

This paper introduces the Transformer, a novel neural network architecture based solely on attention mechanisms. It avoids recurrence and convolutions entirely, offering significant improvements in machine translation quality while being more parallelizable and requiring less training time. The core innovation is the self-attention mechanism, which allows the model to weigh the importance of different parts of the input sequence when processing each element.