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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Влияние персональных характеристик талантов на добровольное увольнение: кейс международного аэропорта Шереметьево

Вестник Санкт-Петербургского университета. Серия 8. Менеджмент. 2022. Т. 21. № 2. С. 214–236.
Volchenko T.

The article discusses the use of personal characteristics of talented employees in assessing the likelihood of their voluntary turnover. Despite a growing number of publications on talent management issues, most of the works focus on studying institutional conditions or corporate management practices. At the same time, a scant attention is paid to the peculiarities of talented employees’ labor behavior, including a critical problem for organizations in talent management — voluntary turnover. The paper aims to investigate the influence of the personal characteristics of talented employees on their decision to resign voluntarily. The theoretical part of the work is based on the model of an objective view on understanding qualified employees as those who have a particular set of characteristics that can determine their behavior regardless of the organizational context. In addition to the main socio-demographic and professional aspects of talents, the work uses non-cognitive personality parameters described by the “Big Five” model. The empirical part of the study is based on the data from a survey of 180 employees which was included in the talent management program of Sheremetyevo Airport. The results confirmed the influence of socio-demographic and non-cognitive characteristics on the likelihood of talented employees’ voluntary turnover. Also, some of the parameters, in contrast to the previous studies, have the opposite effect, and talent management programs do not retain talented employees. Despite its novelty, the conclusions of the work are limited because the empirical data was obtained from one though a heterogeneous company by its labor characteristics and the research was conducted during the crisis of 2020. The extension of the sample along with the set of non-cognitive traits can serve as a direction for further studies.

Research target: Economics and Management
Language: Russian
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Keywords: управление талантамиtalent managementcognitive and non-cognitive skillsvoluntary turn-overдобровольное увольнениенекогнитивные характеристики
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