Papers by Abdulmohsen Al-Thubaity

2 papers
LC-Eval: A Bilingual Multi-Task Evaluation Benchmark for Long-Context Understanding (2025.findings-emnlp)

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Challenge: Recent advances in Large Language Models (LLMs) have demonstrated sophisticated capabilities, including the ability to process and comprehend extended contexts.
Approach: They propose a bilingual, multi-task evaluation benchmark designed to evaluate long-context understanding in English and Arabic.
Outcome: The proposed benchmark targets context lengths ranging from 4k to over 128k tokens.
AraEval: An Arabic Multi-Task Evaluation Suite for Large Language Models (2025.emnlp-main)

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Challenge: AraEval is a suite of evaluation tasks designed to assess the advanced knowledge, reasoning, truthfulness, and instruction following capabilities of large language models.
Approach: They propose to use AraEval to assess the advanced knowledge, reasoning, truthfulness, and instruction following capabilities of large language models in the Arabic context.
Outcome: The evaluation suite covers a broad spectrum of domains, including science, history, religion, and literature.

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