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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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Отношение россиян и китайцев к коррупционным практикам: кросс-культурный анализ

Вестник Санкт-Петербургского университета. Серия 12: Социология. 2024. Т. 17. № 1. С. 17–32.
Maksimenko A., Дейнека О. С., Дерюгин П. П., Krylova D., Забелина Е. В.

The article is devoted to a comparative analysis of the attitude of Russians and Chinese towards corrupt practices. The study was conducted anonymously in an online survey using the service https://webanketa.ru. 275 Russians and 105 Chinese took part in it. To determine attitudes towards corrupt practices, the author’s questionnaire was developed, based on the “color” model of Arnold Heidenheimer (2015). The questionnaire consisted of 59 hypothetical situations, to assess the corruption of which a 7-point scale was used. For the Chinese participants in the study, a bilingual philologist translated the questionnaire into Chinese. Reliability testing of the instrument confirmed high consistency of the data (Cronbach's α = 0.962). The results of factor analysis made it possible to identify three factors and confirm the color model (black, gray, white) of the perception of corruption by A. Heidenheimer. The results of the study made it possible to identify both general features and culturally specific features of the perception of corruption. A comparative analysis of the data showed that deviant actions of officials or persons whose social role is strictly regulated in society and presupposes high moral qualities (judge, doctor, policeman, etc.) were assessed by respondents as highly corrupt in both samples. Also, in both national groups, respondents gave lower ratings to the corrupt actions of holders of such social roles as a flight attendant, teacher or coach than to the corrupt actions of officials, who were subject to higher moral requirements. At the same time, respondents from China statistically reliably assessed hypothetical situations of “black corruption” as less corrupt, unlike Russians. “White corruption,” on the contrary, was condemned by the Chinese significantly more than by the Russians. The results obtained reflect the transcendental legitimation of power inherent in the Chinese mentality and the horizontal responsibility captured in the “guanxi“ phenomenon.

Research target: Psychology Sociology (including Demography and Anthropology
Language: Russian
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Keywords: кросс-культурное исследованиеRussianscross-cultural researchChineseкитайцывосприятие коррупциироссиянеperception of corruption“color” model of corruptionhypothetical corruption situations"цветовая" модель коррупциигипотетические коррупционные ситуации
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