The "Attention is All You Need" paper introduced the Transformer, a novel neural network architecture that efficiently handles sequence-to-sequence tasks, such as language translation. It uses an "attention" mechanism to focus on important parts of the input data based on context, which improves performance over previous methods like RNNs and LSTMs. The Transformer has significantly impacted natural language processing and serves as the foundation for models like BERT and GPT.
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