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Found 6 papers, 3 papers with code
The LMU Munich System for the WMT 2021 Large-Scale Multilingual Machine Translation Shared Task
This paper describes the submission of LMU Munich to the WMT 2021 multilingual machine translation task for small track #1, which studies translation between 6 languages (Croatian, Hungarian, Estonian, Serbian, Macedonian, English) in 30 directions.
Extending Multilingual Machine Translation through Imitation Learning
Despite the growing variety of languages supported by existing multilingual neural machine translation (MNMT) models, most of the world's languages are still being left behind.
Mitigating Data Imbalance and Representation Degeneration in Multilingual Machine Translation
Despite advances in multilingual neural machine translation (MNMT), we argue that there are still two major challenges in this area: data imbalance and representation degeneration.
$m^4Adapter$: Multilingual Multi-Domain Adaptation for Machine Translation with a Meta-Adapter
We consider a very challenging scenario: adapting the MNMT model both to a new domain and to a new language pair at the same time.
Improving Both Domain Robustness and Domain Adaptability in Machine Translation
First, we want to reach domain robustness, i. e., we want to reach high quality on both domains seen in the training data and unseen domains.
