All datasets / webis
webis/tldr-17
The declared licence (cc-by-4.0) is classified as permissive.
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- cc-by-4.0, from the tagEvidence: README.md at fa7f50e
- Licence files
- No licence file at the top level of the repositoryEvidence: file list at fa7f50e
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Citation text from the card
@inproceedings{volske-etal-2017-tl,
title = "{TL};{DR}: Mining {R}eddit to Learn Automatic Summarization",
author = {V{"o}lske, Michael and
Potthast, Martin and
Syed, Shahbaz and
Stein, Benno},
booktitle = "Proceedings of the Workshop on New Frontiers in Summarization",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/W17-4508",
doi = "10.18653/v1/W17-4508",
pages = "59--63",
abstract = "Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data. We propose a new method for mining social media for author-provided summaries, taking advantage of the common practice of appending a {``}TL;DR{''} to long posts. A case study using a large Reddit crawl yields the Webis-TLDR-17 dataset, complementing existing corpora primarily from the news genre. Our technique is likely applicable to other social media sites and general web crawls.",
}
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dataset_licence({ "id": "webis/tldr-17" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0