mlsanityData to 7 Oct 2026

adaptNMT: an open-source, language-agnostic development environment for Neural Machine Translation

arXiv 2403.02367 ↗First posted 4 Mar 2024cs.CL cs.AIcited by 2

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Abstract (arXiv)

adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer neural translation models. As an open-source application, it is designed for both technical and non-technical users who work in the field of machine translation. Built upon the widely-adopted OpenNMT ecosystem, the application is particularly useful for new entrants to the field since the setup of the development environment and creation of train, validation and test splits is greatly simplified. Graphing, embedded within the application, illustrates the progress of model training, and SentencePiece is used for creating subword segmentation models. Hyperparameter customization is facilitated through an intuitive user interface, and a single-click model development approach has been implemented. Models developed by adaptNMT can be evaluated using a range of metrics, and deployed as a translation service within the application. To support eco-friendly research in the NLP space, a green report also flags the power consumption and kgCO2 emissions generated during model development. The application is freely available.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 30 of its 64 references that are in the map. First posted on arXiv 4 Mar 2024.

Builds on

30 of 64 references.

References · 30

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18 more
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Cited by year

Citing papers per year: 2024: 2.

2 papers.

  1. 2024Leveraging LLMs for MT in Crisis Scenarios: a blueprint for low-resource languagescited by 1
  2. 2024Design of an Open-Source Architecture for Neural Machine Translationcited by 0