text: 246,121,1224762472814600192,737878789636694016,Kshitij Jain,"Our new paper on Unsupervised Multilingual Alignment using Wasserstein Barycenter is now online on Arxiv <LINK>. In this work, we show that using Wasserstein Barycenter as a pivot/mean language, we are able to achieve state-of-the-art translation accuracies. This work was done in collaboration with Xin Lian (intern at @BorealisAI), Jakub Truszkowski, Pascal Poupart, and Yaoliang Yu.",https://arxiv.org/abs/2002.00743,"We study unsupervised multilingual alignment, the problem of finding word-to-word translations between multiple languages without using any parallel data. One popular strategy is to reduce multilingual alignment to the much simplified bilingual setting, by picking one of the input languages as the pivot language that we transit through. However, it is well-known that transiting through a poorly chosen pivot language (such as English) may severely degrade the translation quality, since the assumed transitive relations among all pairs of languages may not be enforced in the training process. Instead of going through a rather arbitrarily chosen pivot language, we propose to use the Wasserstein barycenter as a more informative ""mean"" language: it encapsulates information from all languages and minimizes all pairwise transportation costs. We evaluate our method on standard benchmarks and demonstrate state-of-the-art performances. ",Unsupervised Multilingual Alignment using Wasserstein Barycenter,2,"['Our new paper on Unsupervised Multilingual Alignment using Wasserstein Barycenter is now online on Arxiv <LINK>. In this work, we show that using Wasserstein Barycenter as a pivot/mean language, we are able to achieve state-of-the-art translation accuracies.', 'This work was done in collaboration with Xin Lian (intern at @BorealisAI), Jakub Truszkowski, Pascal Poupart, and Yaoliang Yu.']",20,02,385