Papers with Mixed Multi-Head Self-Attention

1 papers
Mixed Multi-Head Self-Attention for Neural Machine Translation (D19-56)

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Challenge: Recent advances in neural machine translation have been made in the field of multi-head self-attention and there is no explicit mechanism to ensure that different attention heads capture different features.
Approach: They propose a novel multi-head self-attention model which models not only global and local attention but also forward and backward attention in different attention heads.
Outcome: The proposed model improves on WAT17 English-Japanese and IWSLT14 German-English translation tasks without increasing the number of parameters.

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