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News
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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Изучение и моделирование совместной деятельности в сетевых сообществах

M. : Московский городской педагогический университет, 2024.
Patarakin Y.

The monograph is dedicated to the practice of studying and modeling collaborative activities in the educational process. The foundation of the monograph consists of case studies obtained during training or research. It is intended for students of pedagogical specialties who aim to gain a deeper understanding of the mechanisms that determine the behavior of participants in educational network communities, such as Wiki, Scratch, and MESH. The study of behavior is based on the analysis of traces left by participants on digital objects. These traces allow us to reveal the dynamics of collaborative activity. The book offers open tools for modeling and analyzing collaborative activity, contributing to the development of effective methods of pedagogical practice in the digital space.

Research target: Education Sociology (including Demography and Anthropology
Language: Russian
Full text
Text on another site
Keywords: многоагентное моделированиесетевое сообществоcommunityagent based modelingNetLogoNetlogoSemantic MediaWikiSemantic MediaWiki
Изучение и моделирование совместной деятельности в сетевых сообществах
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