Grammatical Error Correction via Sequence Tagging for Russian

We introduce a modified sequence tagging architecture, proposed in (Omelianchuk et al., 2020), for the Grammatical Error Correction of the Russian language.We propose languagespecific operation set and preprocessing algorithm as well as a classification scheme which makes distinct predictions for insertions and other operations.The best versions of our models outperform previous approaches and set new SOTA on the two Russian GEC benchmarks -RU-Lang8 and GERA, while achieve competitive performance on RULEC-GEC.