@inproceedings{nasyrova-sorokin-2025-grammatical,
title = "Grammatical Error Correction via Sequence Tagging for {R}ussian",
author = "Nasyrova, Regina and
Sorokin, Alexey",
editor = "Zhao, Jin and
Wang, Mingyang and
Liu, Zhu",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-srw.82/",
doi = "10.18653/v1/2025.acl-srw.82",
pages = "1036--1050",
ISBN = "979-8-89176-254-1",
abstract = "We introduce a modified sequence tagging architecture, proposed in (Omelianchuk et al., 2020), for the Grammatical Error Correction of the Russian language. We propose language-specific 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."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="nasyrova-sorokin-2025-grammatical">
<titleInfo>
<title>Grammatical Error Correction via Sequence Tagging for Russian</title>
</titleInfo>
<name type="personal">
<namePart type="given">Regina</namePart>
<namePart type="family">Nasyrova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alexey</namePart>
<namePart type="family">Sorokin</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Jin</namePart>
<namePart type="family">Zhao</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mingyang</namePart>
<namePart type="family">Wang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Zhu</namePart>
<namePart type="family">Liu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Vienna, Austria</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-254-1</identifier>
</relatedItem>
<abstract>We introduce a modified sequence tagging architecture, proposed in (Omelianchuk et al., 2020), for the Grammatical Error Correction of the Russian language. We propose language-specific 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.</abstract>
<identifier type="citekey">nasyrova-sorokin-2025-grammatical</identifier>
<identifier type="doi">10.18653/v1/2025.acl-srw.82</identifier>
<location>
<url>https://aclanthology.org/2025.acl-srw.82/</url>
</location>
<part>
<date>2025-07</date>
<extent unit="page">
<start>1036</start>
<end>1050</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Grammatical Error Correction via Sequence Tagging for Russian
%A Nasyrova, Regina
%A Sorokin, Alexey
%Y Zhao, Jin
%Y Wang, Mingyang
%Y Liu, Zhu
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-254-1
%F nasyrova-sorokin-2025-grammatical
%X We introduce a modified sequence tagging architecture, proposed in (Omelianchuk et al., 2020), for the Grammatical Error Correction of the Russian language. We propose language-specific 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.
%R 10.18653/v1/2025.acl-srw.82
%U https://aclanthology.org/2025.acl-srw.82/
%U https://doi.org/10.18653/v1/2025.acl-srw.82
%P 1036-1050
Markdown (Informal)
[Grammatical Error Correction via Sequence Tagging for Russian](https://aclanthology.org/2025.acl-srw.82/) (Nasyrova & Sorokin, ACL 2025)
ACL
- Regina Nasyrova and Alexey Sorokin. 2025. Grammatical Error Correction via Sequence Tagging for Russian. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 1036–1050, Vienna, Austria. Association for Computational Linguistics.