3 citations · 9 across the 3 of their papers we have counts for
4 papers
Examining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It
Lifeng Han, Gleb Erofeev, Irina Sorokina +2
Pre-trained language models (PLMs) often take advantage of the monolingual and multilingual dataset that is freely available online to acquire general or mixed domain knowledge bef…
Investigating Massive Multilingual Pre-Trained Machine Translation Models for Clinical Domain via Transfer Learning
Lifeng Han, Gleb Erofeev, Irina Sorokina +2
Massively multilingual pre-trained language models (MMPLMs) are developed in recent years demonstrating superpowers and the pre-knowledge they acquire for downstream tasks. This wo…
Measuring Uncertainty in Translation Quality Evaluation (TQE)
Serge Gladkoff, Irina Sorokina, Lifeng Han +1
From both human translators (HT) and machine translation (MT) researchers' point of view, translation quality evaluation (TQE) is an essential task. Translation service providers (…
cushLEPOR: customising hLEPOR metric using Optuna for higher agreement with human judgments or pre-trained language model LaBSE
Lifeng Han, Irina Sorokina, Gleb Erofeev +1
Human evaluation has always been expensive while researchers struggle to trust the automatic metrics. To address this, we propose to customise traditional metrics by taking advanta…