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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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TitleStatusHype
Listening Comprehension over Argumentative Content—0
Logic Pre-Training of Language Models—0
Low-Resource Generation of Multi-hop Reasoning Questions—0
LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehension—0
Machine Reading Comprehension: a Literature Review—0
Machine Reading Comprehension as Data Augmentation: A Case Study on Implicit Event Argument Extraction—0
Machine Reading Comprehension for Answer Re-Ranking in Customer Support Chatbots—0
Machine Reading Comprehension: Generative or Extractive Reader?—0
Machine Reading Comprehension Using Structural Knowledge Graph-aware Network—0
Machine Reading Comprehension using Case-based Reasoning—0
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