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Serge Gladkoff
Serge Gladkoff
CEO, Logrus Global
在 logrusglobal.com 的电子邮件经过验证 - 首页
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Measuring uncertainty in translation quality evaluation (TQE)
S Gladkoff, I Sorokina, L Han, A Alekseeva
arXiv preprint arXiv:2111.07699, 2021
192021
HOPE: A task-oriented and human-centric evaluation framework using professional post-editing towards more effective MT evaluation
S Gladkoff, L Han
arXiv preprint arXiv:2112.13833, 2021
182021
Investigating massive multilingual pre-trained machine translation models for clinical domain via transfer learning
L Han, G Erofeev, I Sorokina, S Gladkoff, G Nenadic
arXiv preprint arXiv:2210.06068, 2022
102022
cushLEPOR: customising hLEPOR metric using optuna for higher agreement with human judgments or pre-trained language model LaBSE
L Han, I Sorokina, G Erofeev, S Gladkoff
arXiv preprint arXiv:2108.09484, 2021
82021
Examining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It
L Han, G Erofeev, I Sorokina, S Gladkoff, G Nenadic
arXiv preprint arXiv:2209.07417, 2022
62022
Neural machine translation of clinical text: an empirical investigation into multilingual pre-trained language models and transfer-learning
L Han, S Gladkoff, G Erofeev, I Sorokina, B Galiano, G Nenadic
Frontiers in Digital Health 6, 1211564, 2024
52024
Predicting Perfect Quality Segments in MT Output with Fine-Tuned OpenAI LLM: Is it possible to capture editing distance patterns from historical data?
S Gladkoff, G Erofeev, L Han, G Nenadic
arXiv preprint arXiv:2308.00158, 2023
42023
Student's t-Distribution: On Measuring the Inter-Rater Reliability When the Observations are Scarce
S Gladkoff, L Han, G Nenadic
arXiv preprint arXiv:2303.04526, 2023
32023
Using massive multilingual pre-trained language models towards real zero-shot neural machine translation in clinical domain
L Han, G Erofeev, I Sorokina, S Gladkoff, G Nenadic
arXiv, 2022
32022
cushLEPOR uses LABSE distilled knowledge to improve correlation with human translation evaluations
G Erofeev, I Sorokina, L Han, S Gladkoff
Association for Computational Linguistics, 2021
32021
Meta-evaluation of translation evaluation methods: a systematic up-to-date overview
L Han, S Gladkoff
Tutorial at LREC2022, Marseille, France, 2022
22022
Monte carlo modelling of confidence intervals in translation quality evaluation (tqe) and post-editing dstance (ped) measurement
A Alekseeva, S Gladkoff, I Sorokina, L Han
22021
A case of application of a new human mt quality evaluation metric in the emt classroom
P Charalampidou, S Gladkoff
New Trends in Translation and Technology (NeTTT) Conference, 161-165, 2022
12022
cushlepor: Customised hlepor metric using labse distilled knowledge model to improve agreement with human judgements
L Han, I Sorokina, G Erofeev, S Gladkoff
Proceedings of the Sixth Conference on Machine Translation, Online …, 2021
12021
The Multi-Range Theory of Translation Quality Measurement: MQM scoring models and Statistical Quality Control
A Lommel, S Gladkoff, A Melby, SE Wright, I Strandvik, K Gasova, ...
arXiv preprint arXiv:2405.16969, 2024
2024
Predictive Data Analytics with AI: assessing the need for post-editing of MT output by fine-tuning OpenAI LLMs
S Gladkoff, G Erofeev, I Sorokina, L Han, G Nenadic
AMTA2023: Generative AI and the Future of Machine Translation, 2023
2023
Application of an industry practical human MT output Quality Evaluation Metric in the EMT classroom
P Charalampidou, S Gladkoff
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