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, while also being more parallelizable and requiring less training time compared to recurrent models. The Transformer's architecture has since become a foundational component in numerous natural language processing tasks, including speech recognition and transcription.