redasers/difraud

400 downloads in 30 days2 likesLast modified 25 Jul 2024View on Hugging Face

The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at f8fa04a
Licence files: LICENSE.txt, detected as mitEvidence: LICENSE.txt at f8fa04a
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

Citation text from the card

If you use any of these resources, please cite our dataset DIFrauD paper:

    @inproceedings{boumber-etal-2024-domain,
    title = "Domain-Agnostic Adapter Architecture for Deception Detection: Extensive Evaluations with the {DIF}rau{D} Benchmark",
    author = "Boumber, Dainis A.  and Qachfar, Fatima Zahra  and Verma, Rakesh",
    editor = "Calzolari, Nicoletta  and Kan, Min-Yen  and Hoste, Veronique  and Lenci, Alessandro  and Sakti, Sakriani  and Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.468",
    pages = "5260--5274"}

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dataset_licence({ "id": "redasers/difraud" })
signal: "permissive"
stated_licence: "mit"
sources: 0