Machine Reading Comprehension (MRC) is a challenging task and hot topic in Natural
Language Processing. The goal of this field is to develop systems for answering the …

In this work, we tackle the problem of machine reading comprehension (MRC) on the Holy
Qur'an to address the lack of Arabic datasets and systems for this important task. We …

Previous machine comprehension (MC) datasets are either too small to train end-to-end
deep learning models, or not difficult enough to evaluate the ability of current MC …

In this paper, we present a novel approach for incorporating external knowledge in
Recurrent Neural Networks (RNNs). We propose the integration of lexicon features into the …

Abstract Reasoning with commonsense knowledge is critical for natural language
understanding. Traditional methods for commonsense machine comprehension mostly only …

In this dissertation, we address the need for an intelligent machine reading at scale (MRS)
Question Answering (QA) system on the Holy Qur'an, given the permanent interest of …

Abstract Machine Reading Comprehension (MRC) is one of the most challenging tasks in
Natural Language Understanding (NLU). In particular, MRC systems typically answer a …

Abstract Recently proposed Story Cloze Test [Mostafazadeh et al., 2016] is a commonsense
machine comprehension application to deal with natural language understanding problem …

This paper focuses on machine reading comprehension for narrative passages. Narrative
passages usually describe a chain of events. When reading this kind of passage, humans …

This paper focuses on the topic of inferential machine comprehension, which aims to fully
understand the meanings of given text to answer generic questions, especially the ones …