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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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Ethnic stereotype content beyond intergroup relations within societies: Exploring the North-South hypothesis for competence and warmth

Cross-Cultural Research. 2022. Vol. 56. No. 4. P. 345–384.
Grigoryev D.

The study extends the approach of the Stereotype Content Model to ethnic stereotype content beyond intergroup relations within societies by exploring the North-South hypothesis for competence and warmth. This paper claims that the “desperate” (resource-poor and unpredictable) of lower-latitude climate regions and “hopeful” (resource-sufficient and stable) ecology higher-latitude climate regions translate into typical aggregate attributes and are afterward generalized to the status of all their residents. Further, people use this information as a diagnostic for judgments about the economic value or burden of ethnic groups in their society. Based on the data about aggregated means of competence and warmth for 77 ethnic groups in 38 regions, the multivariate models show that ethnic groups from warmer climates and from lower wealth countries are given lower evaluation in both competence and warmth stereotypes. However, ethnic groups from more northerly countries are also given a lower evaluation in warmth. Ethnic stereotypes reflect both features of ethnic groups in countries of origin (e.g., the North-South polarization) and group characteristics carried by ethnic groups in new contexts (i.e., intergroup relations). Thus, reactions to ethnic groups seem to differ partly depending on countries of origin mixed in people’s minds with information about geography, climate, and national wealth in the social perception process. Stereotypes associated with ethnic groups across countries to some extent track the stereotypes associated with the ecologies in which these ethnic groups are assumed to predominantly live. This highlights the importance of the establishment or expansion of policies and programs regarding international inequality.

Research target: Social Sciences Psychology Sociology (including Demography and Anthropology Social and Economic Geography (including Urban and Transportation Studies) Other social sciences
Language: English
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Keywords: social perceptioncompetencestereotype content modelwarmthethnic stereotypesNorth-South polarization in stereotypeslatitudinal gradientsinternational inequalityNorth-South divide
Publication based on the results of:
Values, intercultural and socio-economic interaction in the context of ethnic diversity and the COVID-19 pandemic (2022)
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