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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.
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.

 

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Функционирование современного российского телевидения в условиях мультиплатформенности: модель коллаборативного развития медиа

Вестник славянских культур. 2025. Т. 76. С. 9–25.
Yefanov A.

The subject of the research in this article is the features of the functioning of modern Russian television in the context of multi-platform conditions, predetermined by the model of collaborative media development. The theoretical and methodological basis of the study is the concept of receptive aesthetics (G. Blumenberg, G.-G. Gadamer, G.R. Jauss), in the disposition of which the receptive approach is formed, as well as the theory of convergent culture (H. Jenkins). A set of methods is used: modeling; structural analysis; secondary analysis of sociological and statistical data. The chronological framework of the study: 2010s – first half of the 2020s. Based on the results of the study, at the theoretical level, the author's definition of the concept of reception in relation to media communications is put forward, the main properties of receptions are identified, a model of collaborative media development is presented. At the empirical level, appealing to the legacy of Cultural Studies, based on qualitative methodology, the main receptive practices are identified in a certain causal temporal progression. The socio-cultural trends of development of modern Russian television and media industry (mainly audiovisual segment) as a whole are explicated. The limitations of the implemented research are outlined. The perspective of the presented research is built.

Research target: Media and Communications Sociology (including Demography and Anthropology
Language: Russian
DOI
Text on another site
Keywords: телевидениеcollaborationInternettelevisionрецептивная эстетикаreceptive aestheticsмультиплатформенностьИнтернетMulti-Platformколлаборативность
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