# Summer: WeChat Neural Machine Translation Systems for the WMT22 Biomedical Translation Task

arXiv: https://arxiv.org/abs/2211.15022 · HTML: https://mlsanity.com/paper/2211.15022/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 15 references that are in the map.
- First posted on arXiv 28 Nov 2022.

## Builds on (most cited first, 10 of 10)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Neural Machine Translation of Rare Words with Subword Units](https://mlsanity.com/paper/1508.07909/) (2015)
- [Sequence-Level Knowledge Distillation](https://mlsanity.com/paper/1606.07947/) (2016)
- [Improving Neural Machine Translation Models with Monolingual Data](https://mlsanity.com/paper/1511.06709/) (2015)
- [Texygen: A Benchmarking Platform for Text Generation Models](https://mlsanity.com/paper/1802.01886/) (2018)
- [Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation](https://mlsanity.com/paper/1611.04558/) (2016)
- [Selective Knowledge Distillation for Neural Machine Translation](https://mlsanity.com/paper/2105.12967/) (2021)
- [Accelerating Neural Transformer via an Average Attention Network](https://mlsanity.com/paper/1805.00631/) (2018)
- [WeChat Neural Machine Translation Systems for WMT20](https://mlsanity.com/paper/2010.00247/) (2020)
- [WeChat Neural Machine Translation Systems for WMT21](https://mlsanity.com/paper/2108.02401/) (2021)

## Abstract (arXiv)

This paper introduces WeChat's participation in WMT 2022 shared biomedical translation task on Chinese to English. Our systems are based on the Transformer, and use several different Transformer structures to improve the quality of translation. In our experiments, we employ data filtering, data generation, several variants of Transformer, fine-tuning and model ensemble. Our Chinese→English system, named Summer, achieves the highest BLEU score among all submissions.