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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 261–270 of 555 papers

TitleStatusHype
Conversational Machine Comprehension: a Literature Review—0
A Multi-Stage Memory Augmented Neural Network for Machine Reading Comprehension—0
Adaptations of ROUGE and BLEU to Better Evaluate Machine Reading Comprehension Task—0
Increasing the Difficulty of Automatically Generated Questions via Reinforcement Learning with Synthetic Preference—0
Integrated Triaging for Fast Reading Comprehension—0
Controlling Risk of Web Question Answering—0
Continual Machine Reading Comprehension via Uncertainty-aware Fixed Memory and Adversarial Domain Adaptation—0
A Multilingual Reading Comprehension System for more than 100 Languages—0
Continual Domain Adaptation for Machine Reading Comprehension—0
Ask to Learn: A Study on Curiosity-driven Question Generation—0
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