{
 "id": "tasksource/HYPO-L",
 "owner": "tasksource",
 "name": "HYPO-L",
 "downloads": 76,
 "likes": 1,
 "last_modified": "2023-05-31T11:34:17.000Z",
 "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{zhang-wan-2022-mover,\n    title = \"{MOVER}: Mask, Over-generate and Rank for Hyperbole Generation\",\n    author = \"Zhang, Yunxiang  and\n      Wan, Xiaojun\",\n    booktitle = \"Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies\",\n    month = jul,\n    year = \"2022\",\n    address = \"Seattle, United States\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2022.naacl-main.440\",\n    doi = \"10.18653/v1/2022.naacl-main.440\",\n    pages = \"6018--6030\",\n    abstract = \"Despite being a common figure of speech, hyperbole is under-researched in Figurative Language Processing. In this paper, we tackle the challenging task of hyperbole generation to transfer a literal sentence into its hyperbolic paraphrase. To address the lack of available hyperbolic sentences, we construct HYPO-XL, the first large-scale English hyperbole corpus containing 17,862 hyperbolic sentences in a non-trivial way. Based on our corpus, we propose an unsupervised method for hyperbole generation that does not require parallel literal-hyperbole pairs. During training, we fine-tune BART to infill masked hyperbolic spans of sentences from HYPO-XL. During inference, we mask part of an input literal sentence and over-generate multiple possible hyperbolic versions. Then a BERT-based ranker selects the best candidate by hyperbolicity and paraphrase quality. Automatic and human",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "0b26cd45832c21a229044d9d20ea3af412dc00d9",
 "stated_evidence": "https://huggingface.co/datasets/tasksource/HYPO-L/blob/0b26cd45832c21a229044d9d20ea3af412dc00d9/README.md",
 "file_evidence": "https://huggingface.co/datasets/tasksource/HYPO-L/tree/0b26cd45832c21a229044d9d20ea3af412dc00d9",
 "card_nc": false
}