  Automatic text summarization has been studied in a variety of domains and
languages. However, this does not hold for the Russian language. To overcome
this issue, we present Gazeta, the first dataset for summarization of Russian
news. We describe the properties of this dataset and benchmark several
extractive and abstractive models. We demonstrate that the dataset is a valid
task for methods of text summarization for Russian. Additionally, we prove the
pretrained mBART model to be useful for Russian text summarization.
