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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 191–200 of 555 papers

TitleStatusHype
Cross-Task Knowledge Transfer for Query-Based Text Summarization—0
ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task—0
Effective Character-augmented Word Embedding for Machine Reading Comprehension—0
An Intelligent Recommendation-cum-Reminder System—0
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension—0
A Chinese Machine Reading Comprehension Dataset Automatic Generated Based on Knowledge Graph—0
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets—0
Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation—0
Analysing the Effect of Masking Length Distribution of MLM: An Evaluation Framework and Case Study on Chinese MRC Datasets—0
Ensemble Learning-Based Approach for Improving Generalization Capability of Machine Reading Comprehension Systems—0
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