Papers with mask attention mechanism

1 papers
Enhancing Pre-trained Models with Text Structure Knowledge for Question Generation (2022.coling-1)

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Challenge: Existing question generation models treat input passage as a sequence-to-sequence generative task, but they are not aware of text structure.
Approach: They propose to model text structure as answer position and syntactic dependency and propose a mask attention mechanism to make syntaktic structure of input passage accessible.
Outcome: The proposed model outperforms the strong pre-trained model ProphetNet on a SQuAD dataset and achieves competitive results with the state-of-the-art model.

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