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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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TitleStatusHype
An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text—0
Adversarial reading networks for machine comprehension—0
Stochastic Answer Networks for Machine Reading ComprehensionCode0
Dynamic Fusion Networks for Machine Reading Comprehension—0
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world ApplicationsCode0
Keyword-based Query Comprehending via Multiple Optimized-Demand Augmentation—0
Dataset for the First Evaluation on Chinese Machine Reading ComprehensionCode0
Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability—0
A Constituent-Centric Neural Architecture for Reading Comprehension—0
S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension—0
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