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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 511–520 of 555 papers

TitleStatusHype
A Framework for Evaluation of Machine Reading Comprehension Gold StandardsCode0
Is the Understanding of Explicit Discourse Relations Required in Machine Reading Comprehension?Code0
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world ApplicationsCode0
JBNU-CCLab at SemEval-2022 Task 12: Machine Reading Comprehension and Span Pair Classification for Linking Mathematical Symbols to Their DescriptionsCode0
Adversarial Self-Attention for Language UnderstandingCode0
RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing and Instruction-FollowingCode0
Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity LinkingCode0
CliCR: A Dataset of Clinical Case Reports for Machine Reading ComprehensionCode0
The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot TransferCode0
NumNet: Machine Reading Comprehension with Numerical ReasoningCode0
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