Papers by Heriberto Cuayáhuitl

1 papers
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension (D18-1)

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Challenge: Recent deep-learning based models suffer from reasoning over long documents and do not trivially generalize to cases where the answer is not present as a span.
Approach: They propose a novel context zoom-in network (ConZNet) that can skip through irrelevant parts of a document and generate an answer using only the relevant regions of text.
Outcome: The proposed architecture outperforms state-of-the-art results by 12.62% (ROUGE-L) relative improvement on the recently proposed and challenging RC dataset ‘NarrativeQA’.

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