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Machine Reading Comprehension

Machine Reading Comprehension is one of the key problems in Natural Language Understanding, where the task is to read and comprehend a given text passage, and then answer questions based on it.

Source: Making Neural Machine Reading Comprehension Faster

Papers

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Showing 501–510 of 555 papers

TitleStatusHype
A Span-Extraction Dataset for Chinese Machine Reading ComprehensionCode0
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension—0
U-Net: Machine Reading Comprehension with Unanswerable QuestionsCode0
未登錄詞之向量表示法模型於中文機器閱讀理解之應用 (An OOV Word Embedding Framework for Chinese Machine Reading Comprehension) [In Chinese]—0
MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller—0
Listening Comprehension over Argumentative Content—0
Answer-focused and Position-aware Neural Question Generation—0
A Multi-answer Multi-task Framework for Real-world Machine Reading Comprehension—0
Stochastic Answer Networks for SQuAD 2.0Code0
Multi-task Learning with Sample Re-weighting for Machine Reading ComprehensionCode0
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