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 be trained faster and achieves state-of-the-art results in machine translation tasks. The core idea is to weigh the importance of different parts of the input sequence when processing each part, allowing the model to focus on the most relevant information. This approach has since become a foundational component in many natural language processing tasks, including audio and video editing.