28 citations
- Georgia Institute of TechnologyUS2 papers
- Meta (Israel)IL2 papers
- RWTH Aachen UniversityDE2 papers
- Amazon (Germany)DE1 paper
- Amirkabir University of TechnologyIR1 paper
- Association for Computing MachineryUS1 paper
- Brown UniversityUS1 paper
- École Supérieure d'Électronique de l'OuestFR1 paper
- ETH ZurichCH1 paper
- Google (United States)US1 paper
- Hewlett-Packard (United States)US1 paper
- Laboratoire de Recherche en InformatiqueFR1 paper
4 papers · 1 filter
Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer
Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang +4
Complex natural language applications such as speech translation or pivot translation traditionally rely on cascaded models. However, cascaded models are known to be prone to error…
Back-translation for Large-Scale Multilingual Machine Translation
Baohao Liao, Shahram Khadivi, Sanjika Hewavitharana
This paper illustrates our approach to the shared task on large-scale multilingual machine translation in the sixth conference on machine translation (WMT-21). This work aims to bu…
Word-based Domain Adaptation for Neural Machine Translation
Shen Yan, Leonard Dahlmann, Pavel Petrushkov +2
In this paper, we empirically investigate applying word-level weights to adapt neural machine translation to e-commerce domains, where small e-commerce datasets and large out-of-do…
Guided Alignment Training for Topic-Aware Neural Machine Translation
Wenhu Chen, Evgeny Matusov, Shahram Khadivi +1
In this paper, we propose an effective way for biasing the attention mechanism of a sequence-to-sequence neural machine translation (NMT) model towards the well-studied statistical…