76 citations · 148 across the 26 of their papers we have counts for
4 papers · 1 filter
Improving Both Domain Robustness and Domain Adaptability in Machine Translation
Wen Lai, Jindřich Libovický, Alexander Fraser
We consider two problems of NMT domain adaptation using meta-learning. First, we want to reach domain robustness, i.e., we want to reach high quality on both domains seen in the tr…
Why don't people use character-level machine translation?
Jindřich Libovický, Helmut Schmid, Alexander Fraser
We present a literature and empirical survey that critically assesses the state of the art in character-level modeling for machine translation (MT). Despite evidence in the literat…
Improving the Lexical Ability of Pretrained Language Models for Unsupervised Neural Machine Translation
Alexandra Chronopoulou, Dario Stojanovski, Alexander Fraser
Successful methods for unsupervised neural machine translation (UNMT) employ crosslingual pretraining via self-supervision, often in the form of a masked language modeling or a seq…
Neural String Edit Distance
Jindřich Libovický, Alexander Fraser
We propose the neural string edit distance model for string-pair matching and string transduction based on learnable string edit distance. We modify the original expectation-maximi…