?
Conditional Generators of Words Definitions
P. 266–271.
We explore recently introduced definition modeling technique that provided the tool for evaluation of different distributed vector representations of words through modeling dictionary definitions of words. In this work, we study the problem of word ambiguities in definition modeling and propose a possible solution by employing latent variable modeling and soft attention mechanisms. Our quantitative and qualitative evaluation and analysis of the model shows that taking into account words ambiguity and polysemy leads to performance improvement.
In book
Vol. 2: Short Papers. , Association for Computational Linguistics, 2018.
Tatarinov Maksim, Demidovsky Aleksandr, , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог» 2025. Выпуск 23, дополнительный том.: [б.и.], 2025. P. 1123–1132.
This paper investigates definition modeling as an approach to semantic change detection, which offers the advantage of providing human-readable explanations, unlike traditional embedding-based approaches that lack interpretability. Definition modeling leverages large language models to generate dictionary-like definitions based on target words and their contextual usages. Despite its potential, practical evaluations of this method remain scarce. ...
Added: October 23, 2025
Микулинский А. Д., , in: Синергия языков и культур 2022: междисциплинарные исследования.: St. Petersburg: -, 2023. P. 335–351.
The paper is devoted to the issue of the local structure modeling of the eSports commentary spoken genre on an example of the Dota 2 computer discipline. ESports commentary is a spontaneous and creative speech aimed at describing of what is happening on the computer-gaming field. The main factors that force us to study it ...
Added: May 12, 2024
Taktasheva E., Shavrina T., Fenogenova A. et al., , in: Findings of the Association for Computational Linguistics: EMNLP 2022.: Association for Computational Linguistics, 2022. P. 2472–2497.
Recent advances in zero-shot and few-shot learning have shown promise for a scope of research and practical purposes. However, this fast-growing area lacks standardized evaluation suites for non-English languages, hindering progress outside the Anglo-centric paradigm. To address this line of research, we propose TAPE (Text Attack and Perturbation Evaluation), a novel benchmark that includes six ...
Added: September 22, 2023
Tikhonova M., Mikhailov V., Dina Pisarevskaya et al., Natural Language Engineering 2022 P. 1–30
Recent research has reported that standard fine-tuning approaches can be unstable due to being prone to various sources of randomness, including but not limited to weight initialization, training data order, and hardware. Such brittleness can lead to different evaluation results, prediction confidences, and generalization inconsistency of the same models independently fine-tuned under the same experimental setup. ...
Added: May 21, 2022
Kodryan M., Grachev A., Ignatov D. I. et al., , in: Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)Issue W19-43.: Association for Computational Linguistics, 2019. P. 40–48.
Reduction of the number of parameters is one of the most important goals in Deep Learning. In this article we propose an adaptation of Doubly Stochastic Variational Inference for Automatic Relevance Determination (DSVI-ARD) for neural networks compression. We find this method to be especially useful in language modeling tasks, where large number of parameters in ...
Added: November 1, 2019
Grachev A., Ignatov D. I., Savchenko A., Applied Soft Computing Journal 2019 Vol. 79 P. 354–362
Recurrent neural networks have proved to be an effective method for statistical language modeling. However, in practice their memory and run-time complexity are usually too large to be implemented in real-time offline mobile applications. In this paper we consider several compression techniques for recurrent neural networks including Long–Short Term Memory models. We make particular attention ...
Added: June 12, 2019
M.: Russian State University for the Humanitie, 2019.
The book includes 61 reports of the International conference on computer and intellectual technology "Dialogue-2019", representing a wide range of theoretical and applied research in the field of natural language description, modeling of language processes, creating practically applicable computer linguistic technologies. For specialists in the field of theoretical and applied linguistics and intellectual technologies. ...
Added: June 12, 2019
Grachev A., Ignatov D. I., Savchenko A., , in: Pattern Recognition and Machine Intelligence. 7th International Conference, PReMI 2017, Kolkata, India, December 5-8, 2017, Proceedings. Lecture Notes in Computer Science book series (LNCS, volume 10597).: Springer, 2017. P. 351–357.
In this paper, we consider several compression techniques for the language modeling problem based on recurrent neural networks (RNNs). It is known that conventional RNNs, e.g., LSTM-based networks in language modeling, are characterized with either high space complexity or substantial inference time. This problem is especially crucial
for mobile applications, in which the constant interaction with ...
Added: October 14, 2018
Наконечная Е. Т., , in: Proceedings of the 22nd Conference of Open Innovations Association FRUCT.: Jyvaskyla: [б.и.], 2018. P. 361–365.
Статья является продолжением ряда исследований, посвященных изучению ритмики художественной прозы А. С. Пушкина. В работе рассматриваются такие произведения, как «Дубровский», «Пиковая дама», «Капитанская дочка», «Кирджали», «Египетские ночи». Применяется метод отбора «случайных» четырехстопных ямбов. Ритмика стихоподобных фрагментов сравнивается с вероятностно-статистическими моделями распределения стихотворных строк в прозе. В результате анализа случайных стихоподобных фрагментов рассмотрена эволюция ритмики прозы ...
Added: June 12, 2018
Lopukhina A., Лопухин К. А., , in: Electronic lexicography in the 21st century. Proceedings of eLex 2017 conference.: Brno: Lexical Computing CZ s.r.o., 2017. P. 267–280.
In this paper, we investigate several extensions to our prior work on sense frequency estimation for Russian. Our method is based on semantic vectors and is able to achieve good accuracy for sense frequency estimation trained on dictionary entries from the Active Dictionary of Russian and unannotated corpora. We apply our method to verbs and ...
Added: September 27, 2017
Klyshinskiy E., Рысаков С. В., Новые информационные технологии в автоматизированных системах 2016
Статья знакомит читателя с базовыми понятиями параметрической оптимизации. Описывается разработанная модель аппроксимация вероятности, функции-счётчики и коэффициенты корреляции. Небольшое внимание уделено методу полного перебора, в результате работы которого достигнуты новые показатели точности. В конце приведена модификация метода снятия омонимии, разработанная авторами. ...
Added: June 14, 2016
Manakhov P., Ковшов Е. Е., Прикладная информатика 2012 № 3(39) С. 71–81
The article examines the issue of developing models of the text input methods. The urgency of this matter is dictated by the reduction of financial costs of designing new input methods and upgrading existing ones. The article suggests a modeling method, which is verified by a series of experiments. Also the article gives recommendations on ...
Added: January 17, 2015