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20222026
most citedExamining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It

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

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cs.CL2026

Looking under the Wrong Lamppost: On the Limitations of Automated Translation Quality Estimation

Serge Gladkoff, Angelika Vaasa, Sue Ellen Wright +2

Automation of Translation Quality Estimation (QE) has emerged as a widely discussed approach to managing translation quality at scale, and a growing number of tools and technologie…

cs.CL2025

Non-Linear Scoring Model for Translation Quality Evaluation

Serge Gladkoff, Lifeng Han, Katerina Gasova

Analytic Translation Quality Evaluation (TQE), based on Multidimensional Quality Metrics (MQM), traditionally uses a linear error-to-penalty scale calibrated to a reference sample…

cs.CL2024

The Multi-Range Theory of Translation Quality Measurement: MQM scoring models and Statistical Quality Control

Arle Lommel, Serge Gladkoff, Alan Melby +10

The year 2024 marks the 10th anniversary of the Multidimensional Quality Metrics (MQM) framework for analytic translation quality evaluation. The MQM error typology has been widely…

cs.CL2023

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

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.CL20223 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…