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In the context of machine learning, particularly in natural language processing, “attention” refers to mechanisms that allow models to weigh the importance of different input elements when generating outputs. This approach enables models to focus on relevant parts of the input sequence, improving performance in tasks such as translation, summarization, and question-answering.

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