mlsanityData to 7 Oct 2026

The GPT-WritingPrompts Dataset: A Comparative Analysis of Character Portrayal in Short Stories

arXiv 2406.16767 ↗First posted 24 Jun 2024cs.CLcited by 8

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Abstract (arXiv)

The improved generative capabilities of large language models have made them a powerful tool for creative writing and storytelling. It is therefore important to quantitatively understand the nature of generated stories, and how they differ from human storytelling. We augment the Reddit WritingPrompts dataset with short stories generated by GPT-3.5, given the same prompts. We quantify and compare the emotional and descriptive features of storytelling from both generative processes, human and machine, along a set of six dimensions. We find that generated stories differ significantly from human stories along all six dimensions, and that human and machine generations display similar biases when grouped according to the narrative point-of-view and gender of the main protagonist. We release our dataset and code at https://github.com/KristinHuangg/gpt-writing-prompts.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 24 of its 45 references that are in the map. First posted on arXiv 24 Jun 2024.

Builds on

24 of 45 references.

References · 24

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12 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 3.

8 papers.

  1. 2025Prototypical Human-AI Collaboration Behaviors from LLM-Assisted Writing in the Wildcited by 24
  2. 2025Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learningcited by 7
  3. 2025Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstormingcited by 4
  4. 2024Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMscited by 3
  5. 2026Where You Inject Diversity Matters: A Unified Framework for Diverse Generationcited by 2
  6. 2025Zero-Shot Detection of LLM-Generated Code via Approximated Task Conditioningcited by 1
  7. 2026OrchMAS: Orchestrated Reasoning with Multi Collaborative Heterogeneous Scientific Expert Structured Agentscited by 0
  8. 2026Elias in the Lighthouse, Again? Diagnosing Low Diversity in LLM Storiescited by 0