# XNMT: The eXtensible Neural Machine Translation Toolkit

arXiv: https://arxiv.org/abs/1803.00188 · HTML: https://mlsanity.com/paper/1803.00188/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Mar 2018.

## Built on by (most cited first, 14 of 14)

- [Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference?](https://mlsanity.com/paper/2106.01045/) (2021)
- [Vulnerabilities in AI Code Generators: Exploring Targeted Data Poisoning Attacks](https://mlsanity.com/paper/2308.04451/) (2023)
- [Many-to-English Machine Translation Tools, Data, and Pretrained Models](https://mlsanity.com/paper/2104.00290/) (2021)
- [Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translation](https://mlsanity.com/paper/2203.09866/) (2022)
- [Shellcode_IA32: A Dataset for Automatic Shellcode Generation](https://mlsanity.com/paper/2104.13100/) (2021)
- [How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation](https://mlsanity.com/paper/2105.13782/) (2021)
- [Who Evaluates the Evaluators? On Automatic Metrics for Assessing AI-based Offensive Code Generators](https://mlsanity.com/paper/2212.06008/) (2022)
- [Automating the Correctness Assessment of AI-generated Code for Security Contexts](https://mlsanity.com/paper/2310.18834/) (2023)
- [Noisy UGC Translation at the Character Level: Revisiting Open-Vocabulary Capabilities and Robustness of Char-Based Models](https://mlsanity.com/paper/2110.12552/) (2021)
- [Understanding the Impact of UGC Specificities on Translation Quality](https://mlsanity.com/paper/2110.12551/) (2021)
- [Joint Speech Transcription and Translation: Pseudo-Labeling with Out-of-Distribution Data](https://mlsanity.com/paper/2212.09982/) (2022)
- [Enhancing Robustness of AI Offensive Code Generators via Data Augmentation](https://mlsanity.com/paper/2306.05079/) (2023)
- [Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation](https://mlsanity.com/paper/2203.15319/) (2022)
- [Can We Generate Shellcodes via Natural Language? An Empirical Study](https://mlsanity.com/paper/2202.03755/) (2022)

## Abstract (arXiv)

This paper describes XNMT, the eXtensible Neural Machine Translation toolkit. XNMT distin- guishes itself from other open-source NMT toolkits by its focus on modular code design, with the purpose of enabling fast iteration in research and replicable, reliable results. In this paper we describe the design of XNMT and its experiment configuration system, and demonstrate its utility on the tasks of machine translation, speech recognition, and multi-tasked machine translation/parsing. XNMT is available open-source at https://github.com/neulab/xnmt