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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 121–130 of 555 papers

TitleStatusHype
ET5: A Novel End-to-end Framework for Conversational Machine Reading ComprehensionCode0
Explaining Interactions Between Text SpansCode0
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
Entity-Relation Extraction as Multi-Turn Question AnsweringCode0
Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset ConstructionCode0
English Machine Reading Comprehension Datasets: A SurveyCode0
EQuANt (Enhanced Question Answer Network)Code0
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained ModelsCode0
Effective Subword Segmentation for Text ComprehensionCode0
Automatic Task Requirements Writing Evaluation via Machine Reading ComprehensionCode0
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