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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
KLUE: Korean Language Understanding EvaluationCode1
Sentence Extraction-Based Machine Reading Comprehension for Vietnamese—0
Question-Driven Span Labeling Model for Aspect–Opinion Pair Extraction—0
Dependency Parsing as MRC-based Span-Span PredictionCode1
ExpMRC: Explainability Evaluation for Machine Reading ComprehensionCode1
REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-trainingCode0
NLP-IIS@UT at SemEval-2021 Task 4: Machine Reading Comprehension using the Long Document Transformer—0
Improving Cross-Lingual Reading Comprehension with Self-Training—0
VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension—0
Conversational Machine Reading Comprehension for Vietnamese Healthcare TextsCode0
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