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Vaswani, Shazeer, Parmar, Uszkoreit + 4 more
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The Transformer relies entirely on an attention mechanism to draw global dependencies between input and output.
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Paperverse
Influential research, distilled into short summaries.
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The Transformer relies entirely on an attention mechanism to draw global dependencies between input and output.
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Paperverse
Influential research, distilled into short summaries.
Vaswani, Shazeer, Parmar, Uszkoreit + 4 more
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The Transformer relies entirely on an attention mechanism to draw global dependencies between input and output.
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Paperverse
Influential research, distilled into short summaries.
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The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The Transformer relies entirely on an attention mechanism to draw global dependencies between input and output.
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