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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
Feeding What You Need by Understanding What You Learned—0
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning—0
Correcting the Misuse: A Method for the Chinese Idiom Cloze Test—0
ForceReader: a BERT-based Interactive Machine Reading Comprehension Model with Attention Separation—0
FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis Selection—0
FQuAD: French Question Answering Dataset—0
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark—0
A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension—0
Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice machine reading comprehension—0
A Survey on Explainability in Machine Reading Comprehension—0
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