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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 471–480 of 555 papers

TitleStatusHype
Does Structure Matter? Encoding Documents for Machine Reading Comprehension—0
Dual Co-Matching Network for Multi-choice Reading Comprehension—0
Dual Multi-head Co-attention for Multi-choice Reading Comprehension—0
DuReader\_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World Applications—0
Dynamic Fusion Networks for Machine Reading Comprehension—0
ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task—0
Effective Character-augmented Word Embedding for Machine Reading Comprehension—0
emrQA-msquad: A Medical Dataset Structured with the SQuAD V2.0 Framework, Enriched with emrQA Medical Information—0
End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training—0
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension—0
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