Self-Attention
Self-attention is a mechanism in deep learning that allows a model to weigh the importance of different positions of its own input sequence to compute a representation of the sequence. It is a type of attention mechanism that computes the attention weights based on the similarity between each input position and all other positions. Self-attention has been successfully applied in natural language processing tasks such as machine translation, text classification, and language modeling. It has also been used in computer vision tasks such as image captioning and object detection.
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