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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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Computer-Based Creative Thinking Assessment of Schoolchildren without Expert Involvement

Psychology. Journal of the Higher School of Economics. 2025. Vol. 22. No. 2. P. 339–361.
Uglanova I., Tarasov S., Churbanova S., Orel E.

Тhe importance of creativе thinking was highlighted in the modern world by including it into the lists of 21st century skills and educational objective into the national curriculums. To make creativity assessment more widespread in school and educational research, it is necessary to diminish the resource-intensity of the assessment for both educators and students. In modern psychometrics, one of the urgent questions of creativity assessment is the automatic scoring of product outcomes. The automatic scoring increases the potential of scaling up since it does not depend on working hours of human raters and eliminates the bias due to experts’ subjectivity. Automatic scoring goes along with computer-based assessment. The aim of this research is to present the methodology of computer-based creative thinking assessment without human-based ratings. We follow evidence-centered design framework and describe the proficiency model, which is based on the cognitive approach and the concept of structural imagination, and the task models for computer-based assessment with automated scoring. In the empirical part, the factor structure of the tool was shown on a sample of 749 5th-grade students. We discuss the benefits of the proposed approach, such as an increase in ecological validity and a decrease in experts’ efforts. The practical significance is the decrease in workload in creativity assessment in classroom conditions using IT.

Research target: Education Psychology
Language: English
DOI
Text on another site
Keywords: компьютерное тестированиеcreative thinkingкреативное мышлениеэкологическая валидностьecological validityevidence-centered designметод доказательной аргументацииcomputer-based assessment
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