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MuLD: The Multitask Long Document Benchmark [dataset]

MuLD (Multitask Long Document Benchmark) is a set of 6 NLP tasks where the inputs consist of at least 10,000 words. The benchmark covers a wide variety of task types including translation, summarization, question answering, and classification. Additionally there is a range of output lengths from a single word classification label all the way up to an output longer than the input text.

Descriptions

Resource type
Collection
Total Items
14
Size
12.1 GB
Contributors
Creator: Hudson, G Thomas 1
Creator: Al Moubayed, Noura 1
1 Durham University
Research methods
MuLD consists of 6 tasks chosen to span a variety of dataset sizes, genres, and formulations, and are created by filtering, extending, or modifying existing NLP dataset approaches.
Other description
Code published on GitHub:  https://github.com/ghomasHudson/muld
Keyword
NLP
Long documents
Multitask
Subject
Natural language processing (Computer science)
Machine learning
Language
German
English
Cited in
arxiv:2202.07362
Identifier
ark:/32150/r102870v95b
Publisher
Durham University
Date Created
2022-01-01
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