@inproceedings{065d634d74644f2aa809ccade8c39dd8,
title = "VisualSem: A High-quality Knowledge Graph for Vision & Language",
abstract = "An exciting frontier in natural language understanding (NLU) and generation (NLG) calls for (vision-and-) language models that can efficiently access external structured knowledge repositories. However, many existing knowledge bases only cover limited domains, or suffer from noisy data, and most of all are typically hard to integrate into neural language pipelines. To fill this gap, we release VisualSem: a high-quality knowledge graph (KG) which includes nodes with multilingual glosses, multiple illustrative images, and visually relevant relations. We also release a neural multi-modal retrieval model that can use images or sentences as inputs and retrieves entities in the KG. This multi-modal retrieval model can be integrated into any (neural network) model pipeline. We encourage the research community to use VisualSem for data augmentation and/or as a source of grounding, among other possible uses. VisualSem as well as the multi-modal retrieval models are publicly available and can be downloaded in this URL: https://github.com/iacercalixto/visualsem.",
author = "Houda Alberts and Ningyuan Huang and Deshpande, {Yash R.} and Yibo Liu and Kyunghyun Cho and Clara Vania and Iacer Calixto",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics.; 1st Workshop on Multilingual Representation Learning, MRL 2021 ; Conference date: 11-11-2021",
year = "2021",
language = "English (US)",
series = "MRL 2021 - 1st Workshop on Multilingual Representation Learning, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "138--152",
editor = "Duygu Ataman and Alexandra Birch and Alexis Conneau and Orhan Firat and Sebastian Ruder and Sahin, {Gozde Gul}",
booktitle = "MRL 2021 - 1st Workshop on Multilingual Representation Learning, Proceedings of the Conference",
}