Tian Liu
2025
A Survey on LLMs for Story Generation
Maria Teleki
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Vedangi Bengali
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Xiangjue Dong
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Sai Tejas Janjur
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Haoran Liu
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Tian Liu
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Cong Wang
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Ting Liu
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Yin Zhang
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Frank Shipman
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James Caverlee
Findings of the Association for Computational Linguistics: EMNLP 2025
Methods for story generation with Large Language Models (LLMs) have come into the spotlight recently. We create a novel taxonomy of LLMs for story generation consisting of two major paradigms: (i) independent story generation by an LLM, and (ii) author-assistance for story generation – a collaborative approach with LLMs supporting human authors. We compare existing works based on their methodology, datasets, generated story types, evaluation methods, and LLM usage. With a comprehensive survey, we identify potential directions for future work
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- Vedangi Bengali 1
- James Caverlee 1
- Xiangjue Dong 1
- Sai Tejas Janjur 1
- Haoran Liu 1
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