Creating Suspenseful Stories: Iterative Planning with Large Language Models

arXiv:2402.17119v1 Announce Type: new
Abstract: Automated story generation has been one of the long-standing challenges in NLP. Among all dimensions of stories, suspense is very common in human-written stories but relatively under-explored in AI-generated stories. While recent advances in large language models (LLMs) have greatly promoted language generation in general, state-of-the-art LLMs are still unreliable when it comes to suspenseful story generation. We propose a novel iterative-prompting-based planning method that is grounded in two theoretical foundations of story suspense from …

abstract advances art arxiv automated challenges cs.cl dimensions general generated human iterative language language generation language models large language large language models llms nlp planning promoted state stories story type