@inproceedings{c686bb92c2b94a90ae2cf4ef7e8c9660,
title = "Creative storytelling with language models and knowledge graphs",
abstract = "Automated story generation is a popular and well-recognized task in the field of natural language processing. The emergence of pre-trained language models based on large Transformer architectures shows the great capability of text generation. However, language models are limited when the generation requires explicit clues within the context. In this research, we study how to combine knowledge graphs with language models, and build a creative story generation system named DICE. DICE uses external knowledge graphs to provide context clues and implicit knowledge to generate coherent and creative stories. The evaluation shows that our approach can effectively inject the knowledge from knowledge graphs into the stories automatically generated by the language model.",
keywords = "Knowledge graph, Language model, Natural language generation, Story generation",
author = "Xinran Yang and Ilaria Tiddi",
year = "2020",
month = oct,
day = "15",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR-WS",
pages = "1--9",
editor = "Stefan Conrad and Ilaria Tiddi",
booktitle = "CIKMW2020 Proceeding of the CIKM 2020 Workshops",
note = "2020 International Conference on Information and Knowledge Management Workshops, CIKMW 2020 ; Conference date: 19-10-2020 Through 23-10-2020",
}