Papers with gating layer

1 papers
Accelerating Neural Transformer via an Average Attention Network (P18-1)

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Challenge: Using parallelizable attention networks, the neural Transformer is slow to train due to auto-regressive architecture and self-attention in the decoder.
Approach: They propose an average attention network to replace the original self-attention model in the decoder of the neural Transformer.
Outcome: The proposed network can decode sentences over four times faster than the original version with almost no loss in training time and translation performance.

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