{
 "id": "copenlu/spanex",
 "owner": "copenlu",
 "name": "spanex",
 "downloads": 103,
 "likes": 2,
 "last_modified": "2023-12-18T20:12:45.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-classification"
 ],
 "citation": "@inproceedings{choudhury-etal-2023-explaining,\n    title = \"Explaining Interactions Between Text Spans\",\n    author = \"Choudhury, Sagnik  and\n      Atanasova, Pepa  and\n      Augenstein, Isabelle\",\n    editor = \"Bouamor, Houda  and\n      Pino, Juan  and\n      Bali, Kalika\",\n    booktitle = \"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing\",\n    month = dec,\n    year = \"2023\",\n    address = \"Singapore\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2023.emnlp-main.783\",\n    doi = \"10.18653/v1/2023.emnlp-main.783\",\n    pages = \"12709--12730\",\n    abstract = \"Reasoning over spans of tokens from different parts of the input is essential for natural language understanding (NLU) tasks such as fact-checking (FC), machine reading comprehension (MRC) or natural language inference (NLI). However, existing highlight-based explanations primarily focus on identifying individual important features or interactions only between adjacent tokens or tuples of tokens. Most notably, there is a lack of annotations capturing the human decision-making process with respect to the necessary interactions for informed decision-making in such tasks. To bridge this gap, we introduce SpanEx, a multi-annotator dataset of human span interaction explanations for two NLU tasks: NLI and FC. We then investigate the decision-making processes of multiple fine-tuned large language models in terms of the employed connections bet",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "fba13360b70420e10397d77f55b4b62310d74285",
 "stated_evidence": "https://huggingface.co/datasets/copenlu/spanex/blob/fba13360b70420e10397d77f55b4b62310d74285/README.md",
 "file_evidence": "https://huggingface.co/datasets/copenlu/spanex/tree/fba13360b70420e10397d77f55b4b62310d74285",
 "card_nc": false
}