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 more quickly and achieve state-of-the-art results in machine translation tasks. The Transformer's reliance on attention mechanisms allows it to model relationships between words in a sentence regardless of their distance, making it particularly effective for capturing long-range dependencies. This breakthrough has paved the way for numerous advancements in natural language processing, including large language models.