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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
HRCA+: Advanced Multiple-choice Machine Reading Comprehension Method—0
Explicit Contextual Semantics for Text Comprehension—0
Improved Synthetic Training for Reading Comprehension—0
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding—0
Improving Cross-Lingual Reading Comprehension with Self-Training—0
Improving Machine Reading Comprehension via Adversarial Training—0
Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge—0
Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning—0
Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite—0
Improving Pre-Trained Multilingual Models with Vocabulary Expansion—0
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