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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 181–190 of 555 papers

TitleStatusHype
Act-Aware Slot-Value Predicting in Multi-Domain Dialogue State TrackingCode0
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
Dual Ask-Answer Network for Machine Reading ComprehensionCode0
Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading ComprehensionCode0
EMBRACE: Evaluation and Modifications for Boosting RACECode0
Ellipsis Resolution as Question Answering: An EvaluationCode0
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world ApplicationsCode0
Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity LinkingCode0
Effective Subword Segmentation for Text ComprehensionCode0
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