@inproceedings{df86377cfbe54f1c990f671b1193869b,
title = "Knowledge-enriched visual storytelling",
abstract = "Stories are diverse and highly personalized, resulting in a large possible output space for story generation. Existing end-to-end approaches produce monotonous stories because they are limited to the vocabulary and knowledge in a single training dataset. This paper introduces KG-Story, a three-stage framework that allows the story generation model to take advantage of external Knowledge Graphs to produce interesting stories. KG-Story distills a set of representative words from the input prompts, enriches the word set by using external knowledge graphs, and finally generates stories based on the enriched word set. This distill-enrich-generate framework allows the use of external resources not only for the enrichment phase, but also for the distillation and generation phases. In this paper, we show the superiority of KG-Story for visual storytelling, where the input prompt is a sequence of five photos and the output is a short story. Per the human ranking evaluation, stories generated by KG-Story are on average ranked better than that of the state-of-the-art systems. Our code and output stories are available at https://github.com/zychen423/KE-VIST.",
author = "Hsu, {Chao Chun} and Chen, {Zi Yuan} and Hsu, {Chi Yang} and Li, {Chih Chia} and Lin, {Tzu Yuan} and Huang, {Ting Hao} and Ku, {Lun Wei}",
note = "Funding Information: This research is partially supported by Ministry of Science and Technology, Taiwan under the project contract 108-2221-E-001-012-MY3, 108-2634-F-001-004-, and the Seed Grant (2019) from the College of Information Sciences and Technology (IST), Pennsylvania State University. Publisher Copyright: Copyright {\textcopyright} 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 34th AAAI Conference on Artificial Intelligence, AAAI 2020 ; Conference date: 07-02-2020 Through 12-02-2020",
year = "2020",
language = "English (US)",
series = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",
publisher = "AAAI press",
pages = "7952--7960",
booktitle = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",
}