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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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Между сопротивлением изменениям и готовностью к ним: библиометрический анализ

Организационная психология. 2023. Т. 13. № 4. С. 141–166.
Bagrationi K.

Abstract. Purpose. To investigate the approaches to resistance to change and readiness for change, focusing on their distinctions. Methodology and study design. Bibliometric analysis of publications related to attitudes toward organizational changes from 1948 to 2022, identifying the main research directions and their key aspects, comparing concepts and approaches, and revealing the main differences between overcoming resistance and fostering readiness for change. The study utilized co-citation analysis and thematic analysis. Findings. Four main research streams related to resistance to change and readiness for change were identified: 1) "individualpsychological" stream, 2) "group" stream, 3) "institutional and strategic" stream, and 4) "agency" stream. It was found that resistance to change and readiness for change have different prerequisites. Conclusions and implications for practice. The study highlights the differences in approaches to dealing with resistance to change and unpreparedness for change. Overcoming resistance to change is reactive and requires active involvement from the leader, for example, demonstrating transformational behavior, supporting employees, and resolving conflicts. This sets it apart from the proactive creation of readiness for change, which can primarily focus on informing employees.

Research target: Psychology Economics and Management Sociology (including Demography and Anthropology
Language: Russian
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Keywords: лидерствоорганизационная психологияleadershipсопротивление изменениямresistance to changeготовность к изменениямorganizational psychologyreadiness for changeattitude towards changeотношение к изменениям
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