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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
End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training—0
Seeing the World through Text: Evaluating Image Descriptions for Commonsense Reasoning in Machine Reading Comprehension—0
Read and Reason with MuSeRC and RuCoS: Datasets for Machine Reading Comprehension for Russian—0
A Multilingual Reading Comprehension System for more than 100 Languages—0
Multi-choice Relational Reasoning for Machine Reading Comprehension—0
Incorporating Syntax and Frame Semantics in Neural Network for Machine Reading Comprehension—0
ForceReader: a BERT-based Interactive Machine Reading Comprehension Model with Attention Separation—0
Graph-Based Knowledge Integration for Question Answering over Dialogue—0
SQL Generation via Machine Reading ComprehensionCode0
Bi-directional CognitiveThinking Network for Machine Reading Comprehension—0
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