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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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TitleStatusHype
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches—0
App-Aware Response Synthesis for User Reviews—0
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension—0
Event Extraction as Machine Reading Comprehension—0
Event Detection via Derangement Reading Comprehension—0
FQuAD: French Question Answering Dataset—0
BUAP: Evaluating Features for Multilingual and Cross-Level Semantic Textual Similarity—0
Answer Uncertainty and Unanswerability in Multiple-Choice Machine Reading Comprehension—0
EveMRC: A Two-stage Evidence Modeling For Multi-choice Machine Reading Comprehension—0
Evaluation of Instruction-Following Ability for Large Language Models on Story-Ending Generation—0
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