{
 "id": "AUEB-NLP/lar-echr",
 "owner": "AUEB-NLP",
 "name": "lar-echr",
 "downloads": 349,
 "likes": 3,
 "last_modified": "2025-05-29T20:27:28.000Z",
 "stated_licence": "cc-by-nc-sa-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "question-answering"
 ],
 "citation": "@inproceedings{chlapanis-etal-2024-lar,\n    title = \"{LAR}-{ECHR}: A New Legal Argument Reasoning Task and Dataset for Cases of the {E}uropean Court of Human Rights\",\n    author = \"Chlapanis, Odysseas S.  and\n      Galanis, Dimitrios  and\n      Androutsopoulos, Ion\",\n    editor = \"Aletras, Nikolaos  and\n      Chalkidis, Ilias  and\n      Barrett, Leslie  and\n      Goanț{\\u{a}}, C{\\u{a}}t{\\u{a}}lina  and\n      Preoțiuc-Pietro, Daniel  and\n      Spanakis, Gerasimos\",\n    booktitle = \"Proceedings of the Natural Legal Language Processing Workshop 2024\",\n    month = nov,\n    year = \"2024\",\n    address = \"Miami, FL, USA\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2024.nllp-1.22/\",\n    doi = \"10.18653/v1/2024.nllp-1.22\",\n    pages = \"267--279\",\n    abstract = \"We present Legal Argument Reasoning (LAR), a novel task designed to evaluate the legal reasoning capabilities of Large Language Models (LLMs). The task requires selecting the correct next statement (from multiple choice options) in a chain of legal arguments from court proceedings, given the facts of the case. We constructed a dataset (LAR-ECHR) for this task using cases from the European Court of Human Rights (ECHR). We evaluated seven general-purpose LLMs on LAR-ECHR and found that (a) the ranking of the models is aligned with that of LegalBench, an established US-based legal reasoning benchmark, even though LAR-ECHR is based on EU law, (b) LAR-ECHR distinguishes top mode",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.",
 "revision": "3204a623238a3a589a595de58e1e78b7e11cde6b",
 "stated_evidence": "https://huggingface.co/datasets/AUEB-NLP/lar-echr/blob/3204a623238a3a589a595de58e1e78b7e11cde6b/README.md",
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 "card_nc": false
}