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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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Система поиска документов, релевантных заданному тексту

С. 266–269.
Полушин Г. В.
RELEVANT DOCUMENTS SEARCH SYSTEM   The article is dedicated to the relevant documents search process automation. Relevant literature search is a non-trivial task, as it requires time and imposes certain requirements to the reader. The paper proposes methods to minimize efforts required to find relevant literatureand to automatize the search process. The analysis of existing software solutions for extracting keywords from texts in Russian is given. Method of extracting key phrases fromRussian text using metrics TF-IDF is described. Method of automatic search of relevant documents with the extracted keywords using a free search engine for full texts of scientific publications of all formats and disciplines Google Scholar is also described. In practice, the system can be used by students, teachers and all who are engaged in scientific activities.   Key words: keywords extraction, automatic search, text processing
Language: Russian
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Keywords: keywords extractionautomatic searchtext processingизвлечение ключевых словавтоматизированный поискобработка текста

In book

Математика и междисциплинарные исследования – 2016
Пермь: Пермский государственный национальный исследовательский университет, 2016.
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