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nala-cub/americas_nli

602 downloads in 30 days11 likesLast modified 23 Jan 2024View on Hugging Face

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The checks could not identify a recognised licence ID for at least one declared source dataset.

Declared licence: cc-by-sa-4.0, from the tagEvidence: README.md at 1f3f4fa
Licence files: No licence file at the top level of the repositoryEvidence: file list at 1f3f4fa
Declared sources: 1
Access gated on Hugging Face: No

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

Sources listed in the card metadata

xnlino licence statedUnclearEvidence: README.md at b8dd5d7

Tasks

text-classification

Citation text from the card

@inproceedings{ebrahimi-etal-2022-americasnli,
    title = "{A}mericas{NLI}: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages",
    author = "Ebrahimi, Abteen  and
      Mager, Manuel  and
      Oncevay, Arturo  and
      Chaudhary, Vishrav  and
      Chiruzzo, Luis  and
      Fan, Angela  and
      Ortega, John  and
      Ramos, Ricardo  and
      Rios, Annette  and
      Meza Ruiz, Ivan Vladimir  and
      Gim{\'e}nez-Lugo, Gustavo  and
      Mager, Elisabeth  and
      Neubig, Graham  and
      Palmer, Alexis  and
      Coto-Solano, Rolando  and
      Vu, Thang  and
      Kann, Katharina",
    booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.acl-long.435",
    pages = "6279--6299",
    abstract = "Pretrained multilingual models are able to perform cross-lingual transfer in a zero-shot setting, even for languages unseen during pretraining. However, prior work evaluating performance on unseen languages has largely been limited to low-level, syntactic tasks, and it remains unclear if zero-shot learning of high-level, semantic tasks is possible for unseen languages. To explore this question, we present AmericasNLI, an extension of XNLI (Conneau et al., 2018) to 10

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dataset_licence({ "id": "nala-cub/americas_nli" })
signal: "unclear"
stated_licence: "cc-by-sa-4.0"
sources: 1