Papers with dynamic mask attention network

1 papers
Mask Attention Networks: Rethinking and Strengthen Transformer (2021.naacl-main)

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Challenge: Existing research explores to enhance the two sublayers separately to improve the capability of Transformer for text representation.
Approach: They propose to combine SAN and Feed-Forward Networks to create a dynamic mask attention network with a learnable mask matrix which can model localness adaptively.
Outcome: The proposed model outperforms the original Transformer on translation and text summarization tasks.

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