| mgpt: Few-shot learners go multilingual O Shliazhko, A Fenogenova, M Tikhonova, A Kozlova, V Mikhailov, ... Transactions of the Association for Computational Linguistics 12, 58-79, 2024 | 150 | 2024 |
| RussianSuperGLUE: A Russian language understanding evaluation benchmark T Shavrina, A Fenogenova, A Emelyanov, D Shevelev, E Artemova, ... arXiv preprint arXiv:2010.15925, 2020 | 84 | 2020 |
| 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 | 38 | 2023 |
| Mera: A comprehensive llm evaluation in russian A Fenogenova, A Chervyakov, N Martynov, A Kozlova, M Tikhonova, ... arXiv preprint arXiv:2401.04531, 2024 | 11 | 2024 |
| NLP methods for automatic candidate’s CV segmentation M Tikhonova, A Gavrishchuk 2019 International Conference on Engineering and Telecommunication (EnT), 1-5, 2019 | 10 | 2019 |
| The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design A Snegirev, M Tikhonova, A Maksimova, A Fenogenova, A Abramov arXiv preprint arXiv:2408.12503, 2024 | 7 | 2024 |
| TAPE: Assessing few-shot Russian language understanding E Taktasheva, T Shavrina, A Fenogenova, D Shevelev, N Katricheva, ... arXiv preprint arXiv:2210.12813, 2022 | 7 | 2022 |
| mGPT: few-shot learners go multilingual (2022) O Shliazhko, A Fenogenova, M Tikhonova, V Mikhailov, A Kozlova, ... URL https://arxiv. org/abs/2204.07580, 0 | 7 | |
| Russian superglue 1.1: Revising the lessons not learned by russian nlp models A Fenogenova, M Tikhonova, V Mikhailov, T Shavrina, A Emelyanov, ... arXiv preprint arXiv:2202.07791, 2022 | 5 | 2022 |
| Continuous prompt tuning for russian: how to learn prompts efficiently with rugpt3? N Konodyuk, M Tikhonova International Conference on Analysis of Images, Social Networks and Texts, 30-40, 2021 | 4 | 2021 |
| Ad astra or astray: Exploring linguistic knowledge of multilingual BERT through NLI task M Tikhonova, V Mikhailov, D Pisarevskaya, V Malykh, T Shavrina Natural Language Engineering 29 (3), 554-583, 2023 | 3 | 2023 |
| Dish-ID: A neural-based method for ingredient extraction and further recipe suggestion I Shchuka, S Miftakhov, V Patrushev, M Tikhonova, A Fenogenova 2020 international conference engineering and telecommunication (En&T), 1-5, 2020 | 3 | 2020 |
| Parameter-Efficient Tuning of Transformer Models for Anglicism Detection and Substitution in Russian [C] D Lukichev, D Kryanina, A Bystrova, A Fenogenova, M Tikhonova Proceedings of the International Conference “Dialogue 2023, 2023 | 2 | 2023 |
| Text Mining for Evaluation of Candidates Based on Their CVs M Tikhonova Analysis of Images, Social Networks and Texts: 8th International Conference …, 2020 | 2 | 2020 |
| Ad astra or astray: exploring linguistic knowledge of multilingual BERT through NLI task–CORRIGENDUM M Tikhonova, V Mikhailov, D Pisarevskaya, V Malykh, T Shavrina Natural Language Engineering 29 (4), 1198-1198, 2023 | 1 | 2023 |
| MMTEB: Massive Multilingual Text Embedding Benchmark K Enevoldsen, I Chung, I Kerboua, M Kardos, A Mathur, D Stap, J Gala, ... arXiv preprint arXiv:2502.13595, 2025 | | 2025 |
| Long Input Benchmark for Russian Analysis I Churin, M Apishev, M Tikhonova, D Shevelev, A Bulatov, Y Kuratov, ... arXiv preprint arXiv:2408.02439, 2024 | | 2024 |
| Industry vs Academia: Running a Course on Transformers in Two Setups I Nikishina, M Tikhonova, V Chekalina, A Zaytsev, A Vazhentsev, ... Proceedings of the Sixth Workshop on Teaching NLP, 7-22, 2024 | | 2024 |
| is the Best Approach for Discovering V Nikonova¹, M Tikhonova Analysis of Images, Social Networks and Texts: 11th International Conference …, 2024 | | 2024 |
| MOROCCO: Model Resource Comparison Framework V Malykh, A Kukushkin, M Tikhonova, T Shavrina International Conference on Data Analytics and Management in Data Intensive …, 2023 | | 2023 |
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