SweSAT-1.0: The Swedish University Entrance Exam as a Benchmark for Large Language Models

Murathan Kurfalı, Shorouq Zahra, Evangelia Gogoulou, Luise Dürlich, Fredrik Carlsson, Joakim Nivre


Abstract
This introduces SweSAT-1.0, a new benchmark dataset created from the Swedish university entrance exam (Högskoleprovet) to assess large language models in Swedish. The current version of the benchmark includes 867 questions across six different tasks, including reading comprehension, mathematical problem solving, and logical reasoning. We find that some widely used open-source and commercial models excel in verbal tasks, but we also see that all models, even the commercial ones, struggle with reasoning tasks in Swedish. We hope that SweSAT-1.0 will facilitate research on large language models for Swedish by enriching the breadth of available tasks, offering a challenging evaluation benchmark that is free from any translation biases.
Anthology ID:
2025.nodalida-1.36
Volume:
Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)
Month:
march
Year:
2025
Address:
Tallinn, Estonia
Editors:
Richard Johansson, Sara Stymne
Venue:
NoDaLiDa
SIG:
Publisher:
University of Tartu Library
Note:
Pages:
331–339
Language:
URL:
https://aclanthology.org/2025.nodalida-1.36/
DOI:
Bibkey:
Cite (ACL):
Murathan Kurfalı, Shorouq Zahra, Evangelia Gogoulou, Luise Dürlich, Fredrik Carlsson, and Joakim Nivre. 2025. SweSAT-1.0: The Swedish University Entrance Exam as a Benchmark for Large Language Models. In Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025), pages 331–339, Tallinn, Estonia. University of Tartu Library.
Cite (Informal):
SweSAT-1.0: The Swedish University Entrance Exam as a Benchmark for Large Language Models (Kurfalı et al., NoDaLiDa 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.nodalida-1.36.pdf