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OpenStaxQA: A multilingual dataset based on open-source college textbooks

arXiv 2510.06239 ↗First posted 3 Oct 2025cs.CLcited by 0

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Abstract (arXiv)

We present OpenStaxQA, an evaluation benchmark specific to college-level educational applications based on 43 open-source college textbooks in English, Spanish, and Polish, available under a permissive Creative Commons license. We finetune and evaluate large language models (LLMs) with approximately 7 billion parameters on this dataset using quantized low rank adapters (QLoRa). Additionally we also perform a zero-shot evaluation on the AI2 reasoning challenge dev dataset in order to check if OpenStaxQA can lead to an improved performance on other tasks. We also discuss broader impacts relevant to datasets such as OpenStaxQA.

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References · 2

  1. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,710
  2. 2021Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Docited by 178

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