# OpenNMT: Neural Machine Translation Toolkit

arXiv: https://arxiv.org/abs/1805.11462 · HTML: https://mlsanity.com/paper/1805.11462/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 May 2018.

## Built on by (most cited first, 27 of 27)

- [Neural Machine Translation for Low-Resource Languages: A Survey](https://mlsanity.com/paper/2106.15115/) (2021)
- [Incorporating Residual and Normalization Layers into Analysis of Masked Language Models](https://mlsanity.com/paper/2109.07152/) (2021)
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- [Congolese Swahili Machine Translation for Humanitarian Response](https://mlsanity.com/paper/2103.10734/) (2021)
- [Noisy UGC Translation at the Character Level: Revisiting Open-Vocabulary Capabilities and Robustness of Char-Based Models](https://mlsanity.com/paper/2110.12552/) (2021)
- [Central Kurdish machine translation: First large scale parallel corpus and experiments](https://mlsanity.com/paper/2106.09325/) (2021)
- [Accelerating the inference of string generation-based chemical reaction models for industrial applications](https://mlsanity.com/paper/2407.09685/) (2024)
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- [Understanding the Impact of UGC Specificities on Translation Quality](https://mlsanity.com/paper/2110.12551/) (2021)
- [TextBox 2.0: A Text Generation Library with Pre-trained Language Models](https://mlsanity.com/paper/2212.13005/) (2022)
- [Translating synthetic natural language to database queries: a polyglot deep learning framework](https://mlsanity.com/paper/2104.07010/) (2021)
- [Small Batch Sizes Improve Training of Low-Resource Neural MT](https://mlsanity.com/paper/2203.10579/) (2022)
- [PharmMT: A Neural Machine Translation Approach to Simplify Prescription Directions](https://mlsanity.com/paper/2204.03830/) (2022)
- [Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation](https://mlsanity.com/paper/2205.08722/) (2022)
- [Limitations of Religious Data and the Importance of the Target Domain: Towards Machine Translation for Guinea-Bissau Creole](https://mlsanity.com/paper/2504.02674/) (2025)
- [Do RNN States Encode Abstract Phonological Processes?](https://mlsanity.com/paper/2104.00789/) (2021)
- [Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish](https://mlsanity.com/paper/2205.15599/) (2022)
- [KATSum: Knowledge-aware Abstractive Text Summarization](https://mlsanity.com/paper/2212.03371/) (2022)
- [Previously on... Automating Code Review](https://mlsanity.com/paper/2508.18003/) (2025)
- [An Exploratory Study on Utilising the Web of Linked Data for Product Data Mining](https://mlsanity.com/paper/2109.01411/) (2021)
- [ViNMT: Neural Machine Translation Toolkit](https://mlsanity.com/paper/2112.15272/) (2021)
- [Can the Language of the Collation be Translated into the Language of the Stemma? Using Machine Translation for Witness Localization](https://mlsanity.com/paper/2206.05603/) (2022)
- [FFN: a Fine-grained Chinese-English Financial Domain Parallel Corpus](https://mlsanity.com/paper/2406.18856/) (2024)
- [Time Is Effort: Estimating Human Post-Editing Time for Grammar Error Correction Tool Evaluation](https://mlsanity.com/paper/2510.04394/) (2025)
- [Template-Free Retrosynthesis with Graph-Prior Augmented Transformers](https://mlsanity.com/paper/2512.10770/) (2025)

## Abstract (arXiv)

OpenNMT is an open-source toolkit for neural machine translation (NMT). The system prioritizes efficiency, modularity, and extensibility with the goal of supporting NMT research into model architectures, feature representations, and source modalities, while maintaining competitive performance and reasonable training requirements. The toolkit consists of modeling and translation support, as well as detailed pedagogical documentation about the underlying techniques. OpenNMT has been used in several production MT systems, modified for numerous research papers, and is implemented across several deep learning frameworks.