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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 91–100 of 555 papers

TitleStatusHype
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading ComprehensionCode0
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained ModelsCode0
Adversarial Self-Attention for Language UnderstandingCode0
Evidence Sentence Extraction for Machine Reading ComprehensionCode0
EQuANt (Enhanced Question Answer Network)Code0
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
Entity-Relation Extraction as Multi-Turn Question AnsweringCode0
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension TaskCode0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
English Machine Reading Comprehension Datasets: A SurveyCode0
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