- Evaluation of machine translation🔍
- Rethinking Machine Learning Benchmarks in the Context of ...🔍
- Make Neural Machine Translation Better🔍
- Evaluating robustness to input perturbations for neural machine ...🔍
- Revisiting Rule|Based and Neural Machine Translation🔍
- Revisiting Low|Resource Neural Machine Translation🔍
- Rethinking the Word|level Quality Estimation for Machine ...🔍
- Machine Translation vs GenAI in Translation🔍
Rethinking the Evaluation of Neural Machine Translation
Evaluation of machine translation - Wikipedia
Various methods for the evaluation for machine translation have been employed. This article focuses on the evaluation of the output of machine translation, ...
Rethinking Machine Learning Benchmarks in the Context of ...
So, how does the evaluation process and ethical ... Improving massively multilingual neural machine translation and zero-shot translation.
Make Neural Machine Translation Better, Faster - A New Way to ...
Neural Machine Translation (NMT) systems produce very high quality translations, and are poised to radically change the professional ...
Neural Machine Translation (NMT) models are sensitive to small perturbations in the input. Robustness to such perturbations is typically measured using ...
Revisiting Rule-Based and Neural Machine Translation - MDPI
This paper proposes a hybrid machine-translation system that combines neural machine translation with well-developed rule-based machine translation to ...
Revisiting Low-Resource Neural Machine Translation: A Case Study
conditions according to (Koehn and Knowles, 2017). NMT, evaluating their importance with abla- tion studies. • we reproduce a comparison of NMT and PB-.
Rethinking the Word-level Quality Estimation for Machine ...
for neural machine translation. In Proceedings of the. 577. 15th Biennial ... Human Evaluation for Machine Translation. Trans-. 635 actions of the ...
Machine Translation vs GenAI in Translation: A Comparative Analysis
This evolution has sparked a key question: does Neural Machine Translation (NMT) or the newer Large Language Models (LLMs) offer superior ...
Rethinking the Design of Sequence-to-Sequence Models for ...
... Translation. (MT) aims to teach machines how to automatically translate across languages. Although the recent success of Machine translation ...
Towards Explainable Evaluation Metrics for Machine Translation
Rethinking ai explainability and plausi- bility. ArXiv ... The inside story: Towards better understanding of machine translation neural evaluation metrics.
Rethinking Data Augmentation for Low-Resource Neural Machine ...
In the context of neural machine translation, this means that the model can be trained to translate multiple languages simultaneously. By doing ...
THUNLP-MT/MT-Reading-List: A machine translation ... - GitHub
Felix Stahlberg. 2020. Neural Machine Translation: A Review and Survey. Journal of Artificial Intelligence Research. Philipp Koehn and Rebecca Knowles. 2017.
Neural Machine Translation: How AI Translates Language
Before this, machine translation operated on a statistical model whereby machine learning depends on a database of previous translations, called ...
Scaling neural machine translation to 200 languages - Nature
The development of neural techniques has opened up new avenues for research in machine translation. Today, neural machine translation (NMT) ...
NAR-Former V2: Rethinking Transformer for Universal Neural ...
Neural network representation learning is the base for evaluating the attributes of different networks via machine learning models. Early methods [7, 20] ...
There are platforms in which MT is integrated with other processes for it to render quality or at the very least, passable translations. Indeed, ...
Rethinking, Researching, and Innovating in the VUCA Era
It covers topics such as neural machine translation, quality evaluation, terminology management, post-editing, crowdsourcing, and ethical issues ...
Finally, evaluation on English-Korean pronoun resolution test suite also shows that our HCE can properly exploit contextual information. 1 Introduction.
Rethinking Benchmarking in NLP - Dynabench
Neural machine translation by jointly · learning to align and translate. arXiv ... Eleventh International Conference on Language Re- sources and Evaluation (LREC ...
Chengqi Zhao - Google Scholar
Rethinking document-level neural machine translation. Z Sun, M Wang, H Zhou, C Zhao, S Huang, J Chen, L Li. arXiv preprint arXiv:2010.08961, 2020. 66, 2020.