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AraLingBench A Human-Annotated Benchmark for Evaluating Arabic Linguistic Capabilities of Large Language Models

📝 Summary:
AraLingBench is a human-annotated benchmark evaluating Arabic LLM linguistic competence using expert-designed questions. It reveals models achieve surface proficiency but lack deep understanding, often relying on memorization rather than true comprehension.

🔹 Publication Date: Published on Nov 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.14295
• PDF: https://arxiv.org/pdf/2511.14295

Datasets citing this paper:
https://huggingface.co/datasets/hammh0a/AraLingBench

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For more data science resources:
https://t.iss.one/DataScienceT

#ArabicNLP #LLMEvaluation #AIResearch #LanguageModels #NLPBenchmarking