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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 451–475 of 555 papers

TitleStatusHype
基於BERT模型之多國語言機器閱讀理解研究(Multilingual Machine Reading Comprehension based on BERT Model)—0
Integrated Triaging for Fast Reading Comprehension—0
Improving Pre-Trained Multilingual Models with Vocabulary Expansion—0
ASGen: Answer-containing Sentence Generation to Pre-Train Question Generator for Scale-up Data in Question Answering—0
KorQuAD1.0: Korean QA Dataset for Machine Reading Comprehension—0
Symmetric Regularization based BERT for Pair-wise Semantic ReasoningCode0
Semantics-aware BERT for Language UnderstandingCode0
Cross-Lingual Machine Reading ComprehensionCode0
Neural Network-based Models with Commonsense Knowledge for Machine Reading Comprehension—0
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning—0
Ellipsis Resolution as Question Answering: An EvaluationCode0
Interactive Machine Comprehension with Information Seeking AgentsCode0
Adversarial Domain Adaptation for Machine Reading Comprehension—0
Query-Based Named Entity Recognition—0
CFO: A Framework for Building Production NLP Systems—0
XCMRC: Evaluating Cross-lingual Machine Reading Comprehension—0
SG-Net: Syntax-Guided Machine Reading ComprehensionCode0
Incorporating Relation Knowledge into Commonsense Reading Comprehension with Multi-task Learning—0
Dialog State Tracking: A Neural Reading Comprehension Approach—0
GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine ComprehensionCode0
Tackling Graphical NLP problems with Graph Recurrent NetworksCode0
An Effective Multi-Stage Approach For Question Answering—0
Neural Machine Reading Comprehension: Methods and Trends—0
CALOR-QUEST : un corpus d'entra\^ et d'\'evaluation pour la compr\'ehension automatique de textes (Machine reading comprehension is a task related to Question-Answering where questions are not generic in scope but are related to a particular document)—0
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
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