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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 211–220 of 555 papers

TitleStatusHype
Bridging the Gap between Language Models and Cross-Lingual Sequence Labeling—0
Data Augmentation for Biomedical Factoid Question AnsweringCode0
Improving Zero-Shot Event Extraction via Sentence Simplification—0
Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension—0
Lite Unified Modeling for Discriminative Reading ComprehensionCode0
VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehension—0
Feeding What You Need by Understanding What You Learned—0
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension TaskCode0
Deep Understanding based Multi-Document Machine Reading Comprehension—0
Pretraining without Wordpieces: Learning Over a Vocabulary of Millions of Words—0
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