mlsanityData to 7 Oct 2026

Understanding the Role of Temperature in Diverse Question Generation by GPT-4

arXiv 2404.09366 ↗First posted 14 Apr 2024cs.CL cs.AIcited by 5

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 3 of its 6 references that are in the map. First posted on arXiv 14 Apr 2024.

Builds on

3 of 6 references.

References · 3

  1. 2022Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Bookcited by 84
  2. 2023A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Educationcited by 34
  3. 2023Can We Trust AI-Generated Educational Content? Comparative Analysis of Human and AI-Generated Learning Resourcescited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

  1. 2025Can Large Language Models Match Tutoring System Adaptivity? A Benchmarking Studycited by 17
  2. 2025Ontologies in Design: How Imagining a Tree Reveals Possibilites and Assumptions in Large Language Modelscited by 3
  3. 2025EvoGPT: Leveraging LLM-Driven Seed Diversity to Improve Search-Based Test Suite Generationcited by 2
  4. 2025Grade Guard: A Smart System for Short Answer Automated Gradingcited by 0
  5. 2026Language-Aware Token Boosting: LLM Language Confusion Reduction Without Tuningcited by 0