Attention is All You Need

This paper introduces the Transformer, a novel neural network architecture based solely on attention mechanisms. It avoids using 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 architectures. Its self-attention mechanism allows for parallelization and models relationships between all words in a sentence directly, capturing long-range dependencies more effectively.