Automatic Story Generation: Challenges and Attempts

Amal Alabdulkarim; Siyan Li; Xiangyu Peng

Automatic Story Generation: Challenges and Attempts

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arxiv 2102.12634 v1 pith:GNWYLKPE submitted 2021-02-25 cs.CL

Amal Alabdulkarim , Siyan Li , Xiangyu Peng This is my paper · ORCID

classification cs.CL

keywords challengesgenerationstoryautomaticexploreresearchaddressedadvancements

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The scope of this survey paper is to explore the challenges in automatic story generation. We hope to contribute in the following ways: 1. Explore how previous research in story generation addressed those challenges. 2. Discuss future research directions and new technologies that may aid more advancements. 3. Shed light on emerging and often overlooked challenges such as creativity and discourse.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation
cs.CL 2025-06 conditional novelty 5.0 of 10

A plot-node and knowledge-graph guided LLM framework that generates long stories and reports high preference win rates over strong baselines, though with evaluation confounds.

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