# CUNI systems for WMT21: Multilingual Low-Resource Translation for Indo-European Languages Shared Task

arXiv: https://arxiv.org/abs/2109.09354 · HTML: https://mlsanity.com/paper/2109.09354/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 24 references that are in the map.
- First posted on arXiv 20 Sep 2021.

## Builds on (most cited first, 17 of 17)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://mlsanity.com/paper/1808.06226/) (2018)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [Beyond English-Centric Multilingual Machine Translation](https://mlsanity.com/paper/2010.11125/) (2020)
- [Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation](https://mlsanity.com/paper/2004.11867/) (2020)
- [Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges](https://mlsanity.com/paper/1907.05019/) (2019)
- [Marian: Fast Neural Machine Translation in C++](https://mlsanity.com/paper/1804.00344/) (2018)
- [Multi-task Sequence to Sequence Learning](https://mlsanity.com/paper/1511.06114/) (2015)
- [Revisiting Low-Resource Neural Machine Translation: A Case Study](https://mlsanity.com/paper/1905.11901/) (2019)
- [Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention](https://mlsanity.com/paper/1908.11365/) (2019)
- [Multilingual Neural Machine Translation with Language Clustering](https://mlsanity.com/paper/1908.09324/) (2019)
- [Zero-Resource Translation with Multi-Lingual Neural Machine Translation](https://mlsanity.com/paper/1606.04164/) (2016)
- [Multi-task Learning for Multilingual Neural Machine Translation](https://mlsanity.com/paper/2010.02523/) (2020)
- [A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation](https://mlsanity.com/paper/1806.06957/) (2018)
- [Scheduled Multi-Task Learning: From Syntax to Translation](https://mlsanity.com/paper/1804.08915/) (2018)
- [Learning to Parse and Translate Improves Neural Machine Translation](https://mlsanity.com/paper/1702.03525/) (2017)
- [A Survey on Multi-output Learning](https://mlsanity.com/paper/1901.00248/) (2019)

## Built on by (most cited first, 1 of 1)

- [Character-level NMT and language similarity](https://mlsanity.com/paper/2308.04398/) (2023)

## Abstract (arXiv)

This paper describes Charles University submission for Multilingual Low-Resource Translation for Indo-European Languages shared task at WMT21. We competed in translation from Catalan into Romanian, Italian and Occitan. Our systems are based on shared multilingual model. We show that using joint model for multiple similar language pairs improves upon translation quality in each pair. We also demonstrate that chararacter-level bilingual models are competitive for very similar language pairs (Catalan-Occitan) but less so for more distant pairs. We also describe our experiments with multi-task learning, where aside from a textual translation, the models are also trained to perform grapheme-to-phoneme conversion.