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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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Российская школа в период пандемии COVID-19: эффекты первых двух волн и качество образования

Вопросы образования. 2022. № 1. С. 160–188.
Чабан Т. Ю., Рамеева Р. С., Denisov I., Kersha Y., Zvyagintsev R.

International studies about the impact of the COVID-19 pandemic on the quality of general education have yielded contradictory results: educational outcomes have fallen markedly in some countries while remaining more or less constant in others. At the same time, over half of published studies attest to the growth of educational inequality during the pandemic. The present article assesses the impact of the pandemic using the data of a regional monitoring study of all schoolchildren in grades 4, 6 and 8 in the Krasnoyarsk Region in 2019 and 2021. Tests of reading literacy in grades 4 and 6 as well as of science literacy in grade 8 have shown the satisfactory psychometric quality. Multilevel regression analysis was used to show that the level of functional literacy of the “pandemic” cohort of schoolchildren, controlled for contextual characteristics, was significantly lower for students in all grades except grade 4. The biggest loss was found for scientific literacy. No correlation was found between the pandemic effect size and the socioeconomic composition of the class (the gap between children with different SES remains at the same level as it was before the pandemic). The teachers’ opportunity to conduct online classes did not serve to improve the educational outcomes of schoolchildren during the pandemic.

Research target: Education
Language: Russian
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Keywords: читательская грамотностьобразовательные результатыобразовательное неравенствоeducational outcomesшкольное обучение educational inequalityreading literacyестественнонаучная грамотностьпотери в обученииCOVID-19 pandemicscience literacyпандемия COVID-19regional monitoringschool learningsocioeconomic composition of the classсоциально-экономическая композиция классарегиональные мониторинги
Publication based on the results of:
School coping strategies to address the negative impact of the COVID-19 pandemic on the quality of education (2021)
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