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 while being more parallelizable and requiring less training time. The key innovation is the self-attention mechanism, which allows the model to weigh the importance of different parts of the input sequence when processing it, leading to better understanding and generation of text.