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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
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet ExtractionCode1
Biomedical named entity recognition using BERT in the machine reading comprehension frameworkCode1
A Robustly Optimized BMRC for Aspect Sentiment Triplet ExtractionCode1
Clinical Reading Comprehension: A Thorough Analysis of the emrQA DatasetCode1
AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading ComprehensionCode1
Multi-Grained Query-Guided Set Prediction Network for Grounded Multimodal Named Entity RecognitionCode1
An MRC Framework for Semantic Role LabelingCode1
ArabicaQA: A Comprehensive Dataset for Arabic Question AnsweringCode1
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
A Multi-turn Machine Reading Comprehension Framework with Rethink Mechanism for Emotion-Cause Pair ExtractionCode1
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