Understanding the Role of Temperature in Diverse Question Generation by GPT-4
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| author | Agarwal, Arav Mittal, Karthik Doyle, Aidan Sridhar, Pragnya Wan, Zipiao Doughty, Jacob Arthur Savelka, Jaromir Sakr, Majd |
| author_facet | Agarwal, Arav Mittal, Karthik Doyle, Aidan Sridhar, Pragnya Wan, Zipiao Doughty, Jacob Arthur Savelka, Jaromir Sakr, Majd |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_09366 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding the Role of Temperature in Diverse Question Generation by GPT-4 Agarwal, Arav Mittal, Karthik Doyle, Aidan Sridhar, Pragnya Wan, Zipiao Doughty, Jacob Arthur Savelka, Jaromir Sakr, Majd Computation and Language Artificial Intelligence 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. |
| title | Understanding the Role of Temperature in Diverse Question Generation by GPT-4 |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2404.09366 |