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Attention mechanisms allow models to focus on different parts of the input sequence for better context understanding.
Attention mechanisms require the model to process inputs in a strictly sequential manner.
Attention mechanisms can capture long-range dependencies without regard to their positional distance.
Attention mechanisms are only beneficial for language processing tasks.
Attention mechanisms can be integrated with various types of neural networks, including CNNs and RNNs.
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