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

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.