- Abstract: Automatic post-editing (APE) is an important remedy for reducing errors of raw translated text produced by machine translation (MT) systems or software-aided translation. In the paper, we present the first attempt to APE for Vietnamese. Specifically, we construct the first large-scale dataset of 5M Vietnamese translated and corrected sentence pairs. We then apply strong neural MT models to handle the APE task using our constructed dataset. Experimental results from both automatic and human evaluations show the effectiveness of the neural MT models in handling the Vietnamese APE task. To facilitate future research and applications, we publicly release our dataset and baseline checkpoints at: http://url-link.