All datasets / textdetox

textdetox/es_paradetox

8 downloads in 30 days0 likesLast modified 25 Jun 2024View on Hugging Face

Unclear

The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence: openrail++, from the tagEvidence: README.md at a943fa1
Licence files: No licence file at the top level of the repositoryEvidence: file list at a943fa1
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Tasks

text2text-generation

Citation text from the card

@inproceedings{dementieva-etal-2024-multiparadetox,
    title = "{M}ulti{P}ara{D}etox: Extending Text Detoxification with Parallel Data to New Languages",
    author = "Dementieva, Daryna  and
      Babakov, Nikolay  and
      Panchenko, Alexander",
    editor = "Duh, Kevin  and
      Gomez, Helena  and
      Bethard, Steven",
    booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.naacl-short.12",
    pages = "124--140",
    abstract = "Text detoxification is a textual style transfer (TST) task where a text is paraphrased from a toxic surface form, e.g. featuring rude words, to the neutral register. Recently, text detoxification methods found their applications in various task such as detoxification of Large Language Models (LLMs) (Leong et al., 2023; He et al., 2024; Tang et al., 2023) and toxic speech combating in social networks (Deng et al., 2023; Mun et al., 2023; Agarwal et al., 2023). All these applications are extremely important to ensure safe communication in modern digital worlds. However, the previous approaches for parallel text detoxification corpora collection{---}ParaDetox (Logacheva et al., 2022) and APPADIA (Atwell et al., 2022){---}were explored only in mo

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dataset_licence({ "id": "textdetox/es_paradetox" })
signal: "unclear"
stated_licence: "openrail++"
sources: 0