mlsanityData to 14 Oct 2026

Trustworthiness of Children Stories Generated by Large Language Models

arXiv 2308.00073 ↗First posted 25 Jul 2023cs.CLcited by 2

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Abstract (arXiv)

Large Language Models (LLMs) have shown a tremendous capacity for generating literary text. However, their effectiveness in generating children's stories has yet to be thoroughly examined. In this study, we evaluate the trustworthiness of children's stories generated by LLMs using various measures, and we compare and contrast our results with both old and new children's stories to better assess their significance. Our findings suggest that LLMs still struggle to generate children's stories at the level of quality and nuance found in actual stories

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 25 Jul 2023.

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14 of 31 references.

References · 14

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2 more
  1. 2022EtriCA: Event-Triggered Context-Aware Story Generation Augmented by Cross Attentioncited by 17
  2. 2022Little Red Riding Hood Goes Around the Globe:Crosslingual Story Planning and Generation with Large Language Modelscited by 2

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.