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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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The future of agricultural cooperatives in Russia: Does theory matter?

Russian Peasant Studies. 2024. Vol. 9. No. 4. P. 6–20.
Yanbykh R., Lerman Z.

The article aims at identifying theoretical and practical reasons for the failure of the agricultural cooperation development in Russia. Authors suggest that rural cooperatives in Russia do not develop due to the general features of the formation of social capital in the Russian countryside, the lack of necessary institutional conditions, and the wrong idea that cooperatives based on the classical principles of cooperation can operate successfully in the contemporary economy and society. The first theoretical barrier to cooperation is that in the contemporary high-technology agriculture, hybrid structures (cooperatives) are less efficient than the hierarchical one used by agroholdings. The second theoretical barrier is the inconsistency of seven classical principles of cooperation formulated at the time of Raiffeisen (i.e. outdated) with today’s economic realities and their transformations. The third practical barrier is the rapid degradation of rural areas and the low level of trust and interaction between members of agricultural cooperatives, which is why there are no trends of the bottom-up development of cooperation. The authors conclude that a high level of social capital is the necessary condition for cooperation: at the formation stage, this level is high due to interpersonal relationships developed from the informal social interactions of its members and a high level of trust among members and between members and management, but cooperatives start to lose their social capital as they enlarge — the sense of community, trust and mutual assistance disappears, the atmosphere becomes more business-oriented.

Research target: Economics and Management Sociology (including Demography and Anthropology
Language: English
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Keywords: социальный капиталsocial capitalсельскохозяйственные кооперативыagricultural cooperatives Russia Россия
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