| Bloom: A 176b-parameter open-access multilingual language model T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... | 1146 | 2023 |
| To the methodology of corpus construction for machine learning:“Taiga” syntax tree corpus and parser T Shavrina, O Shapovalova Proceedings of “CORPORA-2017” International Conference, 78-84, 2017 | 95 | 2017 |
| mgpt: Few-shot learners go multilingual O Shliazhko, A Fenogenova, M Tikhonova, V Mikhailov, A Kozlova, ... arXiv preprint arXiv:2204.07580, 2022 | 78 | 2022 |
| RussianSuperGLUE: A Russian language understanding evaluation benchmark T Shavrina, A Fenogenova, A Emelyanov, D Shevelev, E Artemova, ... arXiv preprint arXiv:2010.15925, 2020 | 65 | 2020 |
| GRAMEVAL 2020 Shared Task: Russian Full Morphology and Universal Dependencies Parsing VNA Lyashevskaya O. N., Shavrina T. O., Trofimov I. V. Компьютерная лингвистика и интеллектуальные технологии: По материалам …, 2020 | 22* | 2020 |
| MorphoRuEval-2017: an evaluation track for the automatic morphological analysis methods for Russian A Sorokin, T Shavrina, O Lyashevskaya, B Bocharov, S Alexeeva, ... | 21 | 2017 |
| Findings of the the ruatd shared task 2022 on artificial text detection in russian T Shamardina, V Mikhailov, D Chernianskii, A Fenogenova, M Saidov, ... arXiv preprint arXiv:2206.01583, 2022 | 19 | 2022 |
| Spelling correction for morphologically rich language: a case study of russian A Sorokin Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing …, 2017 | 19 | 2017 |
| SpellRuEval: The first competition on automatic spelling correction for Russian A Sorokin, A Baytin, I Galinskaya, E Rykunova, T Shavrina Proceedings of the Annual International Conference “Dialogue 15, 2016 | 17 | 2016 |
| Automatic spelling correction for Russian social media texts A Sorokin, T Shavrina Proceedings of the International Conference “Dialog”, Moscow, 688-701, 2016 | 15 | 2016 |
| Automatic morphological tagging of Russian social media corpora: training and testing D Selegey, T Shavrina, V Selegey, S Sharoff Computational Linguistics and Intellectual Technologies, 589-604, 2016 | 10 | 2016 |
| Danetqa: a yes/no question answering dataset for the Russian language T Glushkova, A Machnev, A Fenogenova, T Shavrina, E Artemova, ... International Conference on Analysis of Images, Social Networks and Texts, 57-68, 2020 | 9 | 2020 |
| Differential approach to web-corpus construction T Shavrina Computational Linguistics and Intellectual Technologies: Proceedings of the …, 2018 | 9 | 2018 |
| Text collections for evaluation of Russian morphological taggers O Lyashevskaya, V Bocharov, A Sorokin, T Shavrina, D Granovsky, ... Journal of Linguistics/Jazykovedný casopis 68 (2), 258-267, 2017 | 7 | 2017 |
| Корпус с автоматически снятой морфологической неоднозначностью: к методике лингвистических исследований СА Шаров, ВИ Беликов, НЮ Копылов, АА Сорокин, ТО Шаврина Компьютерная лингвистика и интеллектуальные технологии. По материалам …, 2015 | 7 | 2015 |
| A family of pretrained transformer language models for Russian D Zmitrovich, A Abramov, A Kalmykov, M Tikhonova, E Taktasheva, ... arXiv preprint arXiv:2309.10931, 2023 | 6 | 2023 |
| TAPE: Assessing few-shot Russian language understanding E Taktasheva, T Shavrina, A Fenogenova, D Shevelev, N Katricheva, ... arXiv preprint arXiv:2210.12813, 2022 | 6 | 2022 |
| Modeling advanced lemmatization for Russian language using TnT-Russian morphological parser T Shavrina, A Sorokin Computational Linguistics and Intellectual Technologies: Proceedings of the …, 2015 | 6 | 2015 |
| Wikiomnia: generative qa corpus on the whole russian wikipedia D Pisarevskaya, T Shavrina arXiv preprint arXiv:2204.08009, 2022 | 5 | 2022 |
| How not to lie with a benchmark: Rearranging NLP learderboards T Shavrina, V Malykh | 5 | 2021 |
Alena FenogenovaSberDevices, HSEПодтвержден адрес электронной почты в домене hse.ru
