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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
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading ComprehensionCode0
FedQAS: Privacy-aware machine reading comprehension with federated learningCode0
Act-Aware Slot-Value Predicting in Multi-Domain Dialogue State TrackingCode0
Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading ComprehensionCode0
EQuANt (Enhanced Question Answer Network)Code0
ET5: A Novel End-to-end Framework for Conversational Machine Reading ComprehensionCode0
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
EMBRACE: Evaluation and Modifications for Boosting RACECode0
English Machine Reading Comprehension Datasets: A SurveyCode0
Entity-Relation Extraction as Multi-Turn Question AnsweringCode0
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