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. The Transformer model achieves state-of-the-art results in machine translation tasks, demonstrating superior speed and quality compared to previous models. Its core innovation, the self-attention mechanism, allows the model to weigh the importance of different parts of the input sequence when processing it, making it highly effective for capturing long-range dependencies in text.