3 citations · 4 across the 4 of their papers we have counts for
10 papers · 1 filter
Multilingual Unsupervised Neural Machine Translation with Denoising Adapters
Ahmet Üstün, Alexandre Bérard, Laurent Besacier +1
We consider the problem of multilingual unsupervised machine translation, translating to and from languages that only have monolingual data by using auxiliary parallel language pai…
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters
Asa Cooper Stickland, Alexandre Bérard, Vassilina Nikoulina
Adapter layers are lightweight, learnable units inserted between transformer layers. Recent work explores using such layers for neural machine translation (NMT), to adapt pre-train…
A Multilingual Neural Machine Translation Model for Biomedical Data
Alexandre Bérard, Zae Myung Kim, Vassilina Nikoulina +2
We release a multilingual neural machine translation model, which can be used to translate text in the biomedical domain. The model can translate from 5 languages (French, German,…
Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness
Alexandre Bérard, Ioan Calapodescu, Marc Dymetman +3
We share a French-English parallel corpus of Foursquare restaurant reviews (https://europe.naverlabs.com/research/natural-language-processing/machine-translation-of-restaurant-revi…
Naver Labs Europe's Systems for the Document-Level Generation and Translation Task at WNGT 2019
Fahimeh Saleh, Alexandre Bérard, Ioan Calapodescu +1
Recently, neural models led to significant improvements in both machine translation (MT) and natural language generation tasks (NLG). However, generation of long descriptive summar…
Naver Labs Europe's Systems for the WMT19 Machine Translation Robustness Task
Alexandre Bérard, Ioan Calapodescu, Claude Roux
This paper describes the systems that we submitted to the WMT19 Machine Translation robustness task. This task aims to improve MT's robustness to noise found on social media, like…