English

Towards Inter-character Relationship-driven Story Generation

Computation and Language 2022-11-03 v1

Abstract

In this paper, we introduce the task of modeling interpersonal relationships for story generation. For addressing this task, we propose Relationships as Latent Variables for Story Generation, (ReLiSt). ReLiSt generates stories sentence by sentence and has two major components - a relationship selector and a story continuer. The relationship selector specifies a latent variable to pick the relationship to exhibit in the next sentence and the story continuer generates the next sentence while expressing the selected relationship in a coherent way. Our automatic and human evaluations demonstrate that ReLiSt is able to generate stories with relationships that are more faithful to desired relationships while maintaining the content quality. The relationship assignments to sentences during inference bring interpretability to ReLiSt.

Keywords

Cite

@article{arxiv.2211.00676,
  title  = {Towards Inter-character Relationship-driven Story Generation},
  author = {Anvesh Rao Vijjini and Faeze Brahman and Snigdha Chaturvedi},
  journal= {arXiv preprint arXiv:2211.00676},
  year   = {2022}
}

Comments

EMNLP 2022

R2 v1 2026-06-28T04:57:35.185Z