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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 361–370 of 555 papers

TitleStatusHype
App-Aware Response Synthesis for User Reviews—0
LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical ReasoningCode1
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation ExtractionCode1
Low-Resource Generation of Multi-hop Reasoning Questions—0
Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering—0
A Frame-based Sentence Representation for Machine Reading Comprehension—0
ReCO: A Large Scale Chinese Reading Comprehension Dataset on OpinionCode1
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets—0
New Vietnamese Corpus for Machine Reading Comprehension of Health News Articles—0
On the Multi-Property Extraction and Beyond—0
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