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Main Authors: Agarwal, Arav, Mittal, Karthik, Doyle, Aidan, Sridhar, Pragnya, Wan, Zipiao, Doughty, Jacob Arthur, Savelka, Jaromir, Sakr, Majd
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2404.09366
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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