Machine reading comprehension (MRC), which requires a machine to answer questions
based on a given context, has attracted increasing attention with the incorporation of various …

Machine Reading Comprehension (MRC) is a challenging Natural Language Processing
(NLP) research field with wide real-world applications. The great progress of this field in …

We present a reading comprehension challenge in which questions can only be answered
by taking into account information from multiple sentences. We solicit and verify questions …

Natural language understanding involves reading between the lines with implicit
background knowledge. Current systems either rely on pre-trained language models as the …

Many recent papers address reading comprehension, where examples consist of (question,
passage, answer) tuples. Presumably, a model must combine information from both …

We present MCTest, a freely available set of stories and associated questions intended for
research on the machine comprehension of text. Previous work on machine comprehension …

In order to respond correctly to a free form factual question given a large collection of texts,
one needs to understand the question to a level that allows determining some of the …

The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

This book documents the first serious attempt to construct automatically and use
nonsemantic computational structures for text summarization. Until now, most discourse …

Abstract Systems for Open-Domain Question Answering (OpenQA) generally depend on a
retriever for finding candidate passages in a large corpus and a reader for extracting …