activity
20212024
most citedExamining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It

3 citations · 12 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2024

ACR: A Benchmark for Automatic Cohort Retrieval

Dung Ngoc Thai, Victor Ardulov, Jose Ulises Mena +6

Identifying patient cohorts is fundamental to numerous healthcare tasks, including clinical trial recruitment and retrospective studies. Current cohort retrieval methods in healthc…

cs.CL2023★ 2 cited

Neural Machine Translation of Clinical Text: An Empirical Investigation into Multilingual Pre-Trained Language Models and Transfer-Learning

Lifeng Han, Serge Gladkoff, Gleb Erofeev +3

We conduct investigations on clinical text machine translation by examining multilingual neural network models using deep learning such as Transformer based structures. Furthermore…

cs.CL2023★ 1 cited

MTUncertainty: Assessing the Need for Post-editing of Machine Translation Outputs by Fine-tuning OpenAI LLMs

Serge Gladkoff, Lifeng Han, Gleb Erofeev +2

Translation Quality Evaluation (TQE) is an essential step of the modern translation production process. TQE is critical in assessing both machine translation (MT) and human transla…

cs.CL2022★ 3 cited

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…

cs.CL2022★ 3 cited

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…

cs.CL2021★ 3 cited

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…