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Gapping parsing using pretrained embeddings, attention mechanism and NCRF
P. 203–212.
Emelyanov A., Artemova E.
The article is devoted to the problem of automatic gapping resolution for the Russian language. We use BERT Language Model as embeddings with bidirectional recurrent net- work, attention, and NCRF on the top. Unlike other models these are using BERT, we apply BERT only as embedder without any fine-tuning. As a result, our implementation took second place in the AGRR-2019 competition.
Publication based on the results of:
In book
Issue 18. , M.: Russian State University for the Humanitie, 2019.
Anisimova K., Цифровые гуманитарные исследования 2025 № 2 С. 24–47
Исследование посвящено описанию эмоциональной динамики как проявления художественной структуры русской драмы XVIII–XX вв. на основе автоматической разметки тональности реплик с использованием нейросетевых моделей BERT-архитектуры. Такие модели, дообученные даже на нехудожественных текстах, показывают удовлетворительные результаты при анализе тональности драматических реплик, что было проверено на вручную размеченной тестовой выборке. На основе такой автоматической эмоциональной разметки было показано, ...
Added: February 24, 2026
Voevodina E., Современная зарубежная психология 2025 Т. 14 № 3 С. 172–181
Context and relevance. Well-being research faces methodological limitations of conventional psychometric measures, criticized for poor ecological validity, limited information yield, and inadequate capture of multidimensional construct of well-being. Advanced natural language processing (NLP) technologies offer solutions to these constraints. Objective. To evaluate opportunities and challenges of transformer-based NLP for well-being research. Methods and materials. We conducted an analytical review of ...
Added: October 9, 2025
Mylnikova A., Mylnikov L., Научно-техническая информация. Серия 2: Информационные процессы и системы 2025 № 7 С. 32–44
Рассмотрена модель использования скелетных структур на базе синтаксической разметки для предобработки корпусов текстов перед передачей в нейросетевые модели машинного перевода с целью повышения качества их работы, реализованная с помощью частеречной и синтаксической разметок корпусов текстов, использующих языковую модель, с использованием сети BERT и набора правил. Описана подготовка данных для обучения и предложены способы повышения эффективности ...
Added: September 22, 2025
Storchevoy M., Parshakov P., Paklina S. et al., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2024 Т. 520 № 6 С. 70–81
Measuring a company's ethics is an important element in the mechanism of regulating the behavior of market participants, as it allows consumers and regulators to make better decisions, which has a disciplining effect on companies. We tested various methods of machine analysis of consumer feedback from Russian banks and developed an Ethics Index that allows ...
Added: October 31, 2024
Chistyakova K., Kazakova Tatiana, / NRU HSE. Series WP BRP "Linguistics". 2023. No. 115.
The problem of language models’ interpretation is extensively inspected, but no universal answers have been found. Our study offers to combine widely accepted probing methods with a novel approach to a neural network under investigation. We propose to break grammatical forms on the pre-training step in order to get two "sibling" models, as it casts ...
Added: November 29, 2023
Lobanova P., Bakhtin P., Sergienko Y., IEEE Transactions on Engineering Management 2024 No. 71 P. 11898–11906
Identification of science, technology, and innovation trends is a critical topic both for the scientific community and for companies that develop technologies, work on science and technology policy or invest in high tech. In this research authors demonstrate a novel approach implemented in iFORA system (developed by National Research University Higher School of Economics) using ...
Added: September 8, 2023
Кусакин И. К., Федорец О. В., Romanov A., Научно-техническая информация. Серия 2: Информационные процессы и системы 2022 Т. 12 С. 6–9
This paper discusses modern approaches to natural language processing and appliance of artificial intelligence technologies in the task of classifying scientific texts in Russian. The report contains an analysis of implementations of text vectorization methods, a description of experiments with training various classifier models: from classical machine learning algorithms to neural network transformer architectures. ...
Added: January 31, 2023
Ilia Karpov, Nick Kartashev, , in: Analysis of Images, Social Networks and Texts. 10th International Conference, AIST 2021, Tbilisi, Georgia, December 16–18, 2021, Revised Selected Papers.: Cham: Springer, 2022. P. 1–10.
The ubiquity of the contemporary language understanding tasks gives relevance to the development of generalized, yet highly efficient models that utilize all knowledge, provided by the data source. In this work, we present SocialBERT - the first model that uses knowledge about the author’s position in the network during text analysis. We investigate possible models ...
Added: October 31, 2021
Nikiforovskaya A., Kapralov N., Vlasova A. et al., , in: 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA 2020).: Miami: IEEE, 2020. P. 314–319.
With an ever-increasing number of scientific papers published each year, it becomes more difficult for researchers to explore a field that they are not closely familiar with already. This greatly inhibits the potential for cross-disciplinary research. A traditional introduction into an area may come in the form of a review paper. However, not all areas ...
Added: December 28, 2020
Shavrina T., Fenogenova A., Emelyanov A. et al., , in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).: Association for Computational Linguistics, 2020. P. 4717–4726.
Added: November 22, 2020
Davletov A., Gordeev D., Rei A. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: по материалам ежегодной международной конференции «Диалог» (Москва, 17–20 июня 2020 г.)Issue 19(26): дополнительный том.: -, 2020. P. 187–197.
In this work we present our system for RuREBus shared task held together with Dialog 2020 conference. The task consisted of 3 subtasks: named entity recognition, relation extraction with provided named entity tags and end-to-end relation extraction. Our system took the first and the second place in the first and the second subtasks respectively. For ...
Added: October 10, 2020
Artemova E., Batura T., Sarkisyan V. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» (Москва, 17 июня — 20 июня 2020 г.)Вып. 19(26).: М.: Изд-во РГГУ, 2020. P. 416–432.
В статье представлены результаты соревнования по распознаванию именованных сущностей и извлечению отношений. Целью соревнования является сравнение методов извлечения сущностей и отношений на русском языке в постановке, приближенной к индустриальным задачам. В качестве исходной коллекции текстов использовался корпус Минэкономразвития РФ, содержащий программы стратегического развития. Корпус был размечен в соответствии с инструкцией, разработанной авторами статьи. В процессе ...
Added: June 11, 2020
Emelyanov A., Artemova E., , in: Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing, 2019, Florence, Italy, Association for Computational Linguistics.: Association for Computational Linguistics, 2019. P. 94–99.
In this paper we tackle multilingual named entity recognition task. We use the BERT Language Model as embeddings with bidirectional recurrent network, attention, and NCRF on the top. We apply multilingual BERT only as embedder without any fine-tuning. We test out model on the dataset of the BSNLP shared task, which consists of texts in ...
Added: October 31, 2019