A Character-Centric Creative Story Generation via Imagination
Creative story generation has long been a goal of NLP research. While existing methodologies have aimed to generate long and coherent stories, they fall significantly short of human capabilities in terms of diversity and character depth. To address this, we introduce a novel story generation framewo...
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Zusammenfassung: | Creative story generation has long been a goal of NLP research. While
existing methodologies have aimed to generate long and coherent stories, they
fall significantly short of human capabilities in terms of diversity and
character depth. To address this, we introduce a novel story generation
framework called CCI (Character-centric Creative story generation via
Imagination). CCI features two modules for creative story generation: IG
(Image-Guided Imagination) and MW (Multi-Writer model). In the IG module, we
utilize a text-to-image model to create visual representations of key story
elements, such as characters, backgrounds, and main plots, in a more novel and
concrete manner than text-only approaches. The MW module uses these story
elements to generate multiple persona-description candidates and selects the
best one to insert into the story, thereby enhancing the richness and depth of
the narrative. We compared the stories generated by CCI and baseline models
through statistical analysis, as well as human and LLM evaluations. The results
showed that the IG and MW modules significantly improve various aspects of the
stories' creativity. Furthermore, our framework enables interactive multi-modal
story generation with users, opening up new possibilities for human-LLM
integration in cultural development. Project page : https://www.2024cci.p-e.kr/ |
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DOI: | 10.48550/arxiv.2409.16667 |