Abstract
We conduct a preliminary study of the effect of GPT's temperature parameter on the diversity of GPT4-generated questions. We find that using higher temperature values leads to significantly higher diversity, with different temperatures exposing different types of similarity between generated sets of questions. We also demonstrate that diverse question generation is especially difficult for questions targeting lower levels of Bloom's Taxonomy.
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Agarwal, A., Mittal, K., Doyle, A., Sridhar, P., Wan, Z., Doughty, J. A., … Sakr, M. (2024). Understanding the Role of Temperature in Diverse Question Generation by GPT-4. In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education (Vol. 2, pp. 1550–1551). Association for Computing Machinery, Inc. https://doi.org/10.1145/3626253.3635608
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