  We present our systems participated in the VLSP 2022 machine translation
shared task. In the shared task this year, we participated in both translation
tasks, i.e., Chinese-Vietnamese and Vietnamese-Chinese translations. We build
our systems based on the neural-based Transformer model with the powerful
multilingual denoising pre-trained model mBART. The systems are enhanced by a
sampling method for backtranslation, which leverage large scale available
monolingual data. Additionally, several other methods are applied to improve
the translation quality including ensembling and postprocessing. We achieve
38.9 BLEU on ChineseVietnamese and 38.0 BLEU on VietnameseChinese on the public
test sets, which outperform several strong baselines.
