BloomBench reveals that state-of-the-art VLMs perform well on semantic understanding but struggle with factual recall and creative synthesis, while also showing large English-Arabic performance gaps.
arXiv preprint arXiv:2603.16397 , year=
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Using a 1PL IRT model on real cultural questions across 13 locales, the study identifies a local-language knowledge-access advantage masked by lower proficiency in raw accuracy.
citing papers explorer
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Almieyar-Oryx-BloomBench: A Bilingual Multimodal Benchmark for Cognitively Informed Evaluation of Vision-Language Models
BloomBench reveals that state-of-the-art VLMs perform well on semantic understanding but struggle with factual recall and creative synthesis, while also showing large English-Arabic performance gaps.
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The Masked Advantage: Uncovering Local-Language Access to Cultural Knowledge in LLMs
Using a 1PL IRT model on real cultural questions across 13 locales, the study identifies a local-language knowledge-access advantage masked by lower proficiency in raw accuracy.