@inproceedings{fenogenova-2021-russian,
    title = "{R}ussian Paraphrasers: Paraphrase with Transformers",
    author = "Fenogenova, Alena",
    editor = "Babych, Bogdan  and
      Kanishcheva, Olga  and
      Nakov, Preslav  and
      Piskorski, Jakub  and
      Pivovarova, Lidia  and
      Starko, Vasyl  and
      Steinberger, Josef  and
      Yangarber, Roman  and
      Marci{\'n}czuk, Micha{\l}  and
      Pollak, Senja  and
      P{\v{r}}ib{\'a}{\v{n}}, Pavel  and
      Robnik-{\v{S}}ikonja, Marko",
    booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
    month = apr,
    year = "2021",
    address = "Kiyv, Ukraine",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2021.bsnlp-1.2/",
    pages = "11--19",
    abstract = "This paper studies the generation methods for paraphrasing in the Russian language. There are several transformer-based models (Russian and multilingual) trained on a collected corpus of paraphrases. We compare different models, contrast the quality of paraphrases using different ranking methods and apply paraphrasing methods in the context of augmentation procedure for different tasks. The contributions of the work are the combined paraphrasing dataset, fine-tuned generated models for Russian paraphrasing task and additionally the open source tool for simple usage of the paraphrasers."
}