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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 141–150 of 555 papers

TitleStatusHype
Effect of Visual Extensions on Natural Language Understanding in Vision-and-Language ModelsCode0
Effective Subword Segmentation for Text ComprehensionCode0
Ellipsis Resolution as Question Answering: An EvaluationCode0
Dual Ask-Answer Network for Machine Reading ComprehensionCode0
Conversational Machine Reading Comprehension for Vietnamese Healthcare TextsCode0
Abstract, Rationale, Stance: A Joint Model for Scientific Claim VerificationCode0
DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource DomainCode0
DuReader_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World ApplicationsCode0
Coreference Reasoning in Machine Reading ComprehensionCode0
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world ApplicationsCode0
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