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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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Толерантность к социальным неравенствам в эпоху неопределённости в России - важна ли субъективная мобильность?

Мониторинг общественного мнения: Экономические и социальные перемены. 2022. № 1. С. 39–60.
Mareeva S., Slobodenyuk E., Anikin V. A.

The paper addresses the issue of the perception of social inequality by the population, its dynamics and the role of social mobility as a factor of its differentiation. Based on data from all-Russian representative surveys carried out within the framework of the ISSP international program in 1992-2019 and by FCTAS RAS in 2020, it is shown that in terms of the perception of income inequality by the population, the situation resembles the one seen in the 1990s, during a completely different stage of the country's development. The overwhelming majority of Russians today continue to perceive income inequality as excessively high and unfair. Such perceptions as well as the associated high demand for redistribution do not differ in socio-demographic or socio-economic groups. The experience of social mobility does not lead to significant differentiation in this respect as well; effect of expected mobility in the medium term is also weak. Only short-term expectations “work” relatively noticeably in this regard: if they are positive, then they reduce the negative perception of income inequality and the demand for redistribution. As for the perception of non-monetary inequalities, the normative ideas about which of them should be minimized to achieve social justice turn out to be similar in groups with different directions of expected or experienced mobility. This allows us to conclude that the perception of both monetary and non-monetary inequalities, as well as demand for their reduction, are to a greater extent formed on the basis of normative ideas about the appropriate structure of society and an assessment of its compliance with the observed reality, than on the basis of the individual situation, including expected or experienced mobility.

Research target: Social Sciences Sociology (including Demography and Anthropology Economics and Management
Language: Russian
Full text
DOI
Keywords: социальная мобильностьsocial mobilityнеравенство доходовincome inequalityнемонетарные неравенстваСубъективное восприятие неравенстваnon-monetary inequalitysubjective perception of inequality
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