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 outperform existing models in machine translation tasks while being more parallelizable and requiring significantly less time to train. The Transformer's attention mechanism allows it to focus on different parts of the input sequence when producing each output, capturing long-range dependencies more effectively.