Papers by Safaa Taher Abdelfadil

3 papers
Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset (2025.findings-emnlp)

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Challenge: Mainstream large vision-language models (LVLMs) inherently encode cultural biases, highlighting the need for diverse multimodal datasets.
Approach: They propose to construct a large-scale Arabic multimodal dataset and benchmark explicitly designed for cultural understanding.
Outcome: The proposed dataset covers ten culturally significant domains covering all Arab countries and includes two evaluation benchmarks (PEARL and PEARL-LITE) and a specialized subset (PearL-X).
JAWAHER: A Multidialectal Dataset of Arabic Proverbs for LLM Benchmarking (2025.naacl-long)

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Challenge: Recent advances in instruction fine-tuning and alignment methods have enhanced the adaptability of large language models to user preferences.
Approach: They propose a benchmark to assess LLMs’ capacity to comprehend and interpret Arabic proverbs.
Outcome: The proposed model can generate accurate translations, but struggle to produce culturally nuanced and contextually relevant explanations.

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