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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
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained ModelsCode0
What Makes Reading Comprehension Questions Easier?Code0
Stochastic Answer Networks for Machine Reading ComprehensionCode0
EQuANt (Enhanced Question Answer Network)Code0
Entity-Relation Extraction as Multi-Turn Question AnsweringCode0
Dice Loss for Data-imbalanced NLP TasksCode0
FedQAS: Privacy-aware machine reading comprehension with federated learningCode0
Demonstration-based learning for few-shot biomedical named entity recognition under machine reading comprehensionCode0
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
English Machine Reading Comprehension Datasets: A SurveyCode0
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