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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
To Test Machine Comprehension, Start by Defining Comprehension—0
Towards AMR-BR: A SemBank for Brazilian Portuguese Language—0
Towards Building a Robust Knowledge Intensive Question Answering Model with Large Language Models—0
Towards Confident Machine Reading Comprehension—0
Towards Inference-Oriented Reading Comprehension: ParallelQA—0
Towards Medical Machine Reading Comprehension with Structural Knowledge and Plain Text—0
Towards Robust Neural Retrieval Models with Synthetic Pre-Training—0
To What Extent Do Natural Language Understanding Datasets Correlate to Logical Reasoning? A Method for Diagnosing Logical Reasoning.—0
Transfer Learning Enhanced Single-choice Decision for Multi-choice Question Answering—0
Trigger-free Event Detection via Derangement Reading Comprehension—0
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