{
    "Name": "Dolphin",
    "Volume": 40.0,
    "Unit": "documents",
    "License": "unknown",
    "Link": "https://dolphin.dlnlp.ai/",
    "HF_Link": "",
    "Year": 2023,
    "Domain": [
        "public datasets"
    ],
    "Form": "text",
    "Collection_Style": [
        "manual curation"
    ],
    "Description": "Benchmark for Arabic NLG evaluation",
    "Ethical_Risks": "Low",
    "Provider": [
        "The University of British Columbia",
        "MBZUAI"
    ],
    "Derived_From": [],
    "Paper_Title": "A Challenging and Diverse Benchmark for Arabic NLG",
    "Paper_Link": "https://aclanthology.org/2023.findings-emnlp.98.pdf",
    "Tokenized": false,
    "Host": "other",
    "Access": "Free",
    "Cost": "",
    "Test_Split": true,
    "Tasks": [
        "machine translation",
        "text summarization",
        "question answering",
        "dialogue generation",
        "grammatical error correction"
    ],
    "Venue_Title": "EMNLP",
    "Venue_Type": "conference",
    "Venue_Name": "EMNLP",
    "Authors": [
        "ElMoatez Billah Nagoudi",
        "Abdel Rahim Elmadany",
        "Ahmed Oumar El-Shangiti",
        "Muhammad Abdul-Mageed"
    ],
    "Affiliations": [
        "The University of British Columbia",
        "MBZUAI"
    ],
    "Abstract": "We present Dolphin, a novel benchmark that addresses the need for a natural language generation (NLG) evaluation framework dedicated to the wide collection of Arabic languages and varieties. The proposed benchmark encompasses a broad range of 13 different NLG tasks, including dialogue generation, question answering, machine translation, summarization, among others. Dolphin comprises a substantial corpus of 40 diverse and representative public datasets across 50 test splits, carefully curated to reflect real-world scenarios and the linguistic richness of Arabic. It sets a new standard for evaluating the performance and generalization capabilities of Arabic and multilingual models, promising to enable researchers to push the boundaries of current methodologies.",
    "Subsets": [],
    "Dialect": "mixed",
    "Language": "ar",
    "Script": "Arab",
    "Added_By": "qwen/qwen3.6-35b-a3b"
}