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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.
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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 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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Поведенческая обстановка как основа порядка взаимодействия (на примере исследований бездомности)

Социологические исследования. 2026. № 2. С. 62–73.
Мальков М. Д.

We problematize the foundations of a special type of social order – the interaction order – as conceptualized by sociologist Erving Goffman. The interaction oreder that unfolds in a social situation of physical co-presence may have different foundations: it may be self-sustaining, autonomous and separate from other orders, grounded in the cognitive resources of the participants in the interaction, or provided by the “behavioral setting” in which the interaction takes place. Despite importance and relevance of all three components, we propose to draw on Bruno Latour’s arguments to conceptualize the behavioral setting as a material setting that coordinates and guides the “situational” in interaction and argue that it is the behavioral setting that grounds the interaction order. We propose to place this theoretical discussion in the context of homelessness research that focuses on interactions with people without homes in public spaces. Through these studies, which problematize the boundary between the private and the public, it becomes possible to trace the key role of behavioral settings, which are, in Goffman’s terms, not “merely situated,” but include the situation itself in their framework, guiding and coordinating the order of the “situational” in interaction. The proposed interpretation of the foundation of the interaction order, as localized within a behavioral setting, shifts the theoretical focus of interaction studies toward materiality. At the empirical level, it enables a critical evaluation of those homelessness assistance initiatives that fail to take into account the significance of the behavioral environments within which interactions with homeless individuals take place.

Research target: Social Sciences Sociology (including Demography and Anthropology
Language: Russian
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Keywords: homelessnessбездомностьБруно ЛатурматериальностьИрвинг Гофманпорядок взаимодействияmaterialityErving GoffmanBruno Latourinteraction orderbehavioral settingповеденческая обстановка
Publication based on the results of:
The diversity of forms, effects and barriers to integration of modern Russian society in synchronic and diachronic dimensions (2025)
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