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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 226–250 of 555 papers

TitleStatusHype
Explicit Utilization of General Knowledge in Machine Reading Comprehension—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
Feature-augmented Machine Reading Comprehension with Auxiliary Tasks—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
Feeding What You Need by Understanding What You Learned—0
A Survey on Machine Reading Comprehension Systems—0
Cross-lingual and Cross-domain Evaluation of Machine Reading Comprehension with Squad and CALOR-Quest Corpora—0
ForceReader: a BERT-based Interactive Machine Reading Comprehension Model with Attention Separation—0
FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis Selection—0
FQuAD: French Question Answering Dataset—0
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark—0
A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension—0
Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice machine reading comprehension—0
From Good to Best: Two-Stage Training for Cross-lingual Machine Reading Comprehension—0
Analyse automatique en cadres s\'emantiques pour l'apprentissage de mod\`eles de compr\'ehension de texte (Semantic Frame Parsing for training Machine Reading Comprehension models)—0
G4: Grounding-guided Goal-oriented Dialogues Generation with Multiple Documents—0
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning—0
GAAMA 2.0: An Integrated System that Answers Boolean and Extractive Questions—0
Correcting the Misuse: A Method for the Chinese Idiom Cloze Test—0
A Survey on Explainability in Machine Reading Comprehension—0
Adaptive Bi-directional Attention: Exploring Multi-Granularity Representations for Machine Reading Comprehension—0
Graph-Based Knowledge Integration for Question Answering over Dialogue—0
Graph-combined Coreference Resolution Methods on Conversational Machine Reading Comprehension with Pre-trained Language Model—0
Explicit Contextual Semantics for Text Comprehension—0
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