2021 EACL EACL 2021

What Did This Castle Look like before? Exploring Referential Relations in Naturally Occurring Multimodal Texts

Abstract

AbstractMulti-modal texts are abundant and diverse in structure, yet Language & Vision research of these naturally occurring texts has mostly focused on genres that are comparatively light on text, like tweets. In this paper, we discuss the challenges and potential benefits of a L&V framework that explicitly models referential relations, taking Wikipedia articles about buildings as an example. We briefly survey existing related tasks in L&V and propose multi-modal information extraction as a general direction for future research.

The Questioner
🌉 Interdisciplinary Bridge — Interdisciplinary and Natural Language Processing
🧭 Keyword Pioneer — multimodal text
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio