Papers with proximity-based answer position encoding

1 papers
Improving Question Generation With to the Point Context (D19-1)

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Challenge: Existing sequence-to-sequence neural models may not be able to identify answer-relevant context words for question generation.
Approach: They propose to model the unstructured sentence and the structured answer-relevant relation for question generation by combining to the point context and unstructure.
Outcome: Experiments show that the proposed model improves on the unstructured sentence and the structured answer-relevant relation.

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