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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 131–140 of 555 papers

TitleStatusHype
English Machine Reading Comprehension Datasets: A SurveyCode0
Entity-Relation Extraction as Multi-Turn Question AnsweringCode0
EMBRACE: Evaluation and Modifications for Boosting RACECode0
Adaptive loose optimization for robust question answeringCode0
EQuANt (Enhanced Question Answer Network)Code0
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading ComprehensionCode0
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world ApplicationsCode0
DuReader_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World ApplicationsCode0
DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource DomainCode0
DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource DomainCode0
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