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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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Почему россияне не боятся экономических санкций? Контрриторические стратегии печатных СМИ

Мониторинг общественного мнения: Экономические и социальные перемены. 2016. Т. 131. № 1. С. 256–271.
Kazun A. D.

The article analyzes key strategies of deproblematization of the economic sanctions (and Russian food embargo) which were used in four Russian printed editions from March 2014 to December 2014: Rossiyskaya Gazeta (pro-governmental, 945 articles), Novaya Gazeta (oppositional, 396 articles), Argumenty i Fakty (popular mass newspaper, 258 articles) and Kommersant (business magazine, 1574 articles). Thus, we consider the discussion in the four editions, which could be placed at the poles of the two axes: ideological stance and information category. According to the Title Popularity Ranking (TPR), these prints are leading. Newspapers use a wide range of deproblematization strategies. Some of them are aimed to refute the importance of the problem as a whole (unsympathetic counterrhetoric), others - on proof of insolvency of the proposed ways to solve it (sympathetic counterrhetoric). We conclude that in case of discussion on economic sanctions unsympathetic counterrhetoric prevail. Most popular strategies of deproblematization are “antipatterning”, “telling anecdote” and “counterrhetoric of insincerity” in terms of Ibarra and Kitsuse. The report describes most striking examples of these strategies and makes an inference about their weak and strong points. Also, we make some conclusions about intensity of the discussion on the issue. For example, we deduce that Russian food embargo was more noticeable in the public space than sanctions. The share of articles on sanctions mentioning Crimea steadily declined. At the same time, the share of articles on the subject, mentioning the rouble exchange rate significantly increased.

Research target: Sociology (including Demography and Anthropology Political Science, International Relations, and Public Administration Philology and Linguistics
Priority areas: economics sociology humanitarian
Language: Russian
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DOI
Text on another site
Keywords: санкцииmediapublic opinionСМИpressпрессаsanctionsобщественное мнениепродовольственное эмбарго
Publication based on the results of:
Structural and institutional foundations of modern Russian markets (2016)
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