Cross-lingual representations of words enable us to reason about word meaning in
multilingual contexts and are a key facilitator of cross-lingual transfer when developing …

Vision-and-language pre-training has achieved impressive success in learning multimodal
representations between vision and language. To generalize this success to non-English …

This paper presents the Visual Word Sense Disambiguation (Visual-WSD) task. The
objective of Visual-WSD is to identify among a set of ten images the one that corresponds to …

We introduce a novel multimodal machine translation model that utilizes parallel visual and
textual information. Our model jointly optimizes the learning of a shared visual-language …

In this paper we propose a model to learn multimodal multilingual representations for
matching images and sentences in different languages, with the aim of advancing …

While most machine translation systems to date are trained on large parallel corpora,
humans learn language in a different way: by being grounded in an environment and …

A neural multimodal machine translation (MMT) system is one that aims to perform better
translation by extending conventional text-only translation models with multimodal …

Existing vision-language methods typically support two languages at a time at most. In this
paper, we present a modular approach which can easily be incorporated into existing vision …

There has been a recent spike in interest in multi-modal Language and Vision problems. On
the language side, most of these models primarily focus on English since most multi-modal …

With the aim of promoting and understanding the multilingual version of image search, we
leverage visual object detection and propose a model with diverse multi-head attention to …