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When Dino,...
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TurkishMMLU: Measuring Massive Multitask Language Understanding in Turkish
Arda Yüksel Technical University of Munich Abdullatif Köksal Center for Information and Language Processing, LMU Munich Munich Center for Machine Learning Language Technology Lab, University of Cambridge
arda.yueksel@tum.de, akoksal@cis.lmu.deLütfi Kerem Senel Center for Information and Language Processing, LMU Munich Munich Center for Machine Learning Anna Korhonen Language Technology Lab, University of Cambridge
arda.yueksel@tum.de, akoksal@cis.lmu.deHinrich Schütze Center for Information and Language Processing, LMU Munich Munich Center for Machine Learning
Abstract
Multiple choice question answering tasks evaluate the reasoning, comprehension, and mathematical abilities of Large Language Models (LLMs). While existing benchmarks employ automatic translation for multilingual evaluation, this approach is error-prone and potentially introduces culturally biased questions, especially in social sciences. We introduce the first multitask, multiple-choice Turkish QA benchmark, TurkishMMLU, to evaluate LLMs’ understanding of the Turkish language. TurkishMMLU includes over 10,000 questions, covering 9 different subjects from Turkish high-school education curricula. These questions are written by curric