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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 151–160 of 555 papers

TitleStatusHype
Effect of Visual Extensions on Natural Language Understanding in Vision-and-Language ModelsCode0
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
DRCD: a Chinese Machine Reading Comprehension DatasetCode0
Cross-Lingual Machine Reading ComprehensionCode0
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading ComprehensionCode0
Cross-Lingual Question Answering over Knowledge Base as Reading ComprehensionCode0
A Span-Extraction Dataset for Chinese Machine Reading ComprehensionCode0
DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource DomainCode0
A Multiple Choices Reading Comprehension Corpus for Vietnamese Language EducationCode0
Contextual embedding and model weighting by fusing domain knowledge on Biomedical Question AnsweringCode0
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