Survey maps narrative theory and LLMs for story generation

A new survey paper published on arXiv explores the intersection of narrative theory and large language models (LLMs) for automatic story generation and understanding. The paper categorizes current NLP research based on narratology concepts, highlighting that while understanding tasks are more advanced, generation methods lag in theoretical application and exploring non-fiction narratives. The authors suggest future research should focus on theory-based metrics for narrative attributes, large-scale literary analysis, and generating narratives in situated contexts to validate or refine narrative theories. AI

IMPACT Provides a framework for advancing AI-driven narrative generation and understanding by integrating literary theory.

RANK_REASON The item is a survey paper published on arXiv detailing research at the intersection of narrative theory and LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

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• alphaXiv
• arXiv
• DagsHub
• David T. Liu
• Gotit.pub
• Hugging Face
• large language models
• narratology
• natural language processing
• ScienceCast

• paper
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