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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 276–300 of 555 papers

TitleStatusHype
Connecting Attributions and QA Model Behavior on Realistic CounterfactualsCode1
What does BERT Learn from Arabic Machine Reading Comprehension Datasets?—0
Is the Understanding of Explicit Discourse Relations Required in Machine Reading Comprehension?Code0
Probing into the Root: A Dataset for Reason Extraction of Structural Events from Financial Documents—0
Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehension—0
Robustly Optimized and Distilled Training for Natural Language Understanding—0
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet ExtractionCode1
Cooperative Self-training of Machine Reading ComprehensionCode1
MCR-Net: A Multi-Step Co-Interactive Relation Network for Unanswerable Questions on Machine Reading Comprehension—0
OneStop QAMaker: Extract Question-Answer Pairs from Text in a One-Stop Approach—0
Biomedical Question Answering: A Survey of Approaches and Challenges—0
Self-Teaching Machines to Read and Comprehend with Large-Scale Multi-Subject Question-Answering Data—0
Modeling Context in Answer Sentence Selection Systems on a Latency Budget—0
Weakly Supervised Neuro-Symbolic Module Networks for Numerical Reasoning—0
VisualMRC: Machine Reading Comprehension on Document ImagesCode1
Analyzing Zero-shot Cross-lingual Transfer in Supervised NLP Tasks—0
English Machine Reading Comprehension Datasets: A SurveyCode0
Towards Confident Machine Reading Comprehension—0
ComQA:Compositional Question Answering via Hierarchical Graph Neural NetworksCode1
TSQA: Tabular Scenario Based Question AnsweringCode1
Read, Retrospect, Select: An MRC Framework to Short Text Entity Linking—0
A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis—0
Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering—0
Uncertainty-Based Adaptive Learning for Reading Comprehension—0
Learning to Generate Questions by Recovering Answer-containing Sentences—0
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