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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 451–460 of 555 papers

TitleStatusHype
Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions—0
Cooperative Self-training of Machine Reading Comprehension—0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension—0
Correcting the Misuse: A Method for the Chinese Idiom Cloze Test—0
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning—0
Cross-lingual and Cross-domain Evaluation of Machine Reading Comprehension with Squad and CALOR-Quest Corpora—0
Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation—0
Cross-Task Knowledge Transfer for Query-Based Text Summarization—0
CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment—0
CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking—0
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