Carlos Escolano

(Self-Attentive) Autoencoder-based Universal Language Representation for Machine Translation

2018 · arXiv (Cornell University)

Universal language representation is the holy grail in machine translation (MT). Thanks to the new neural MT approach, it seems that there are good perspectives towards this goal. In this paper, we propose a new …

From bilingual to multilingual neural‐based machine translation by incremental training

2020 · Journal of the Association for Information Science and Technology

Abstract A common intermediate language representation in neural machine translation can be used to extend bilingual systems by incremental training. We propose a new architecture based on introducing an interlingual loss as an additional training …

Gender Bias in Multilingual Neural Machine Translation: The Architecture\n Matters

2020 · arXiv (Cornell University)

Multilingual Neural Machine Translation architectures mainly differ in the\namount of sharing modules and parameters among languages. In this paper, and\nfrom an algorithmic perspective, we explore if the chosen architecture, when\ntrained with the same data, influences …