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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 491–500 of 555 papers

TitleStatusHype
Multi-task Learning with Sample Re-weighting for Machine Reading ComprehensionCode0
Tackling Graphical NLP problems with Graph Recurrent NetworksCode0
Contextual embedding and model weighting by fusing domain knowledge on Biomedical Question AnsweringCode0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
Multi-View Graph Representation Learning for Answering Hybrid Numerical Reasoning QuestionCode0
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning ApproachCode0
A Multiple Choices Reading Comprehension Corpus for Vietnamese Language EducationCode0
Instructive Dialogue Summarization with Query AggregationsCode0
Natural Response Generation for Chinese Reading ComprehensionCode0
Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading ComprehensionCode0
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