This paper surveys 60 English Machine Reading Comprehension datasets, with a view to providing a convenient resource for other researchers interested in this problem. We categorize the datasets according to their question and answer form and compare them across various dimensions including size, vocabulary, data source, method of creation, human performance level, and first question word. Our analysis reveals that Wikipedia is by far the most common data source and that there is a relative lack of why, when, and where questions across datasets
The issue of shortcut learning is widely known in NLP and has been an important research focus in re...
Automatic reading comprehension (RC) systems integrate various kinds of natural language processing ...
In the natural language processing research field, many efforts have been devoted into reading compr...
Reading comprehension is often tested by measuring a person or system’s ability to answer questions ...
Existing analysis work in machine reading comprehension (MRC) is largely concerned with evaluating t...
142 pagesMachine reading comprehension (MRC) tasks have attracted substantial attention from both ac...
Alongside huge volumes of research on deep learning models in NLP in the recent years, there has bee...
Machine comprehension of text is theoverarching goal of a great deal of re-search in natural languag...
Machine Reading Comprehension (MRC) is a challenging task in the field of Natural Language Processin...
Machine reading comprehension (MRC) is a challenging task in the field of artificial intelligence. M...
We present a new dataset of English word recognition times for a total of 62 thousand words, called ...
Machine reading comprehension (MRC) is a research field driven by datasets. The task of MRC is to ma...
Machine Reading Comprehension (MRC) for question answering (QA), which aims to answer a question giv...
Coreference resolution is essential for natural language understanding and has been long studied in ...
The paper presents SberQuAD – a large Russian reading comprehension (RC) dataset created similarly t...
The issue of shortcut learning is widely known in NLP and has been an important research focus in re...
Automatic reading comprehension (RC) systems integrate various kinds of natural language processing ...
In the natural language processing research field, many efforts have been devoted into reading compr...
Reading comprehension is often tested by measuring a person or system’s ability to answer questions ...
Existing analysis work in machine reading comprehension (MRC) is largely concerned with evaluating t...
142 pagesMachine reading comprehension (MRC) tasks have attracted substantial attention from both ac...
Alongside huge volumes of research on deep learning models in NLP in the recent years, there has bee...
Machine comprehension of text is theoverarching goal of a great deal of re-search in natural languag...
Machine Reading Comprehension (MRC) is a challenging task in the field of Natural Language Processin...
Machine reading comprehension (MRC) is a challenging task in the field of artificial intelligence. M...
We present a new dataset of English word recognition times for a total of 62 thousand words, called ...
Machine reading comprehension (MRC) is a research field driven by datasets. The task of MRC is to ma...
Machine Reading Comprehension (MRC) for question answering (QA), which aims to answer a question giv...
Coreference resolution is essential for natural language understanding and has been long studied in ...
The paper presents SberQuAD – a large Russian reading comprehension (RC) dataset created similarly t...
The issue of shortcut learning is widely known in NLP and has been an important research focus in re...
Automatic reading comprehension (RC) systems integrate various kinds of natural language processing ...
In the natural language processing research field, many efforts have been devoted into reading compr...