{
 "id": "SahandSab/EmoBench",
 "owner": "SahandSab",
 "name": "EmoBench",
 "downloads": 253,
 "likes": 2,
 "last_modified": "2025-05-14T07:43:37.000Z",
 "stated_licence": "mit",
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 "licence_name": null,
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 "gated": false,
 "tasks": [
  "question-answering"
 ],
 "citation": "@inproceedings{sabour-etal-2024-emobench,\n    title = \"{E}mo{B}ench: Evaluating the Emotional Intelligence of Large Language Models\",\n    author = \"Sabour, Sahand  and\n      Liu, Siyang  and\n      Zhang, Zheyuan  and\n      Liu, June  and\n      Zhou, Jinfeng  and\n      Sunaryo, Alvionna  and\n      Lee, Tatia  and\n      Mihalcea, Rada  and\n      Huang, Minlie\",\n    editor = \"Ku, Lun-Wei  and\n      Martins, Andre  and\n      Srikumar, Vivek\",\n    booktitle = \"Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)\",\n    month = aug,\n    year = \"2024\",\n    address = \"Bangkok, Thailand\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2024.acl-long.326\",\n    doi = \"10.18653/v1/2024.acl-long.326\",\n    pages = \"5986--6004\",\n    abstract = \"Recent advances in Large Language Models (LLMs) have highlighted the need for robust, comprehensive, and challenging benchmarks. Yet, research on evaluating their Emotional Intelligence (EI) is considerably limited. Existing benchmarks have two major shortcomings: first, they mainly focus on emotion recognition, neglecting essential EI capabilities such as emotion management and thought facilitation through emotion understanding; second, they are primarily constructed from existing datasets, which include frequent patterns, explicit information, and annotation errors, leading to unreliable evaluation. We propose EmoBench, a benchmark that draws ",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "c8a29302139a01cddff1bff90b5434d9b46bd372",
 "stated_evidence": "https://huggingface.co/datasets/SahandSab/EmoBench/blob/c8a29302139a01cddff1bff90b5434d9b46bd372/README.md",
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}