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 achieve superior results in machine translation tasks while being more parallelizable and requiring significantly less training time. The core idea is to weigh the importance of different parts of the input sequence when processing it, allowing the model to focus on the most relevant information for generating the output.