From 5ea9e64f71e0b89baa2d8da07107466672718f2b Mon Sep 17 00:00:00 2001 From: masader-bot Date: Mon, 27 Jul 2026 11:20:39 +0300 Subject: [PATCH] Creating datasets/aragen.json --- datasets/aragen.json | 61 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 61 insertions(+) create mode 100644 datasets/aragen.json diff --git a/datasets/aragen.json b/datasets/aragen.json new file mode 100644 index 00000000..f1acb8c8 --- /dev/null +++ b/datasets/aragen.json @@ -0,0 +1,61 @@ +{ + "Name": "AraGen", + "Dialect Subsets": [], + "HF Link": "", + "Link": "https://huggingface.co/datasets/inceptionai/AraGen", + "License": "unknown", + "Year": 2024, + "Language": "ar", + "Dialect": "Modern Standard Arabic", + "Source": [ + "manual construction" + ], + "Domain": [ + "general" + ], + "Form": "text", + "Annotation Style": [ + "human annotation", + "human validation" + ], + "Description": "AraGen (AraGen-12-24) is a 279-question generative-tasks evaluation benchmark for Arabic LLMs covering question answering, orthographic and grammatical analysis, reasoning, and safety. It was released with the 3C3H evaluation measure and is part of a dynamic leaderboard with rotating three-month blind test sets.", + "Volume": 279.0, + "Unit": "sentences", + "Provider": [ + "Inception", + "MBZUAI" + ], + "Derived From": [], + "Paper Title": "Rethinking LLM Evaluation with 3C3H: AraGen Benchmark and Leaderboard", + "Paper Link": "https://huggingface.co/blog/leaderboard-3c3h-aragen", + "Script": "Arab", + "Tokenized": false, + "Host": "HuggingFace", + "Access": "Free", + "Cost": "", + "Has Splits": false, + "Partial": false, + "Tasks": [ + "question answering", + "grammatical error correction", + "safety evaluation", + "text generation" + ], + "Venue Title": "other", + "Venue Type": "preprint", + "Venue Name": "", + "Authors": [ + "Ali El Filali", + "Neha Sengupta", + "Arwa Abouelseoud", + "Preslav Nakov", + "Cl\u00e9mentine Fourrier" + ], + "Affiliations": [ + "Inception", + "MBZUAI", + "Hugging Face" + ], + "Abstract": "AraGen is a generative-tasks benchmark and leaderboard for Arabic large language models, built around 3C3H, a new evaluation measure for natural language generation. The benchmark comprises 279 custom, mainly human-verified questions spanning four tasks: question answering about Arabic and the Arab world, orthographic and grammatical analysis, reasoning, and safety, with single-turn, conversational, and follow-up interaction formats. The accompanying 3C3H measure scores model responses across six dimensions (Correctness, Completeness, Conciseness, Helpfulness, Honesty, and Harmlessness) using an LLM-as-judge. The leaderboard uses a dynamic strategy in which each test set stays private for a three-month blind-testing cycle before being publicly released and replaced, mitigating data contamination while keeping the evaluation current.", + "Added By": "Kareem Tadros" +} \ No newline at end of file