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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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Storing Multifaceted Ontologies with Natural Language Addressing

P. 62–67.
Lanin V., Lyadova L. N., Shalyaeva I.

Abstract — Multifaceted ontology definition is suggested and an approach to storing multifaceted ontologies in the ontology-driven system for monitoring processes based on Internet sources is presented. This system can be adapted for events analysis and global processes monitoring, for social network analysis and etc. Ontology-driven architecture intends using an ontology. Ontologies are used to search data in the Internet sources with information retrieval tools and to structuring information according to the data structure defined by users. The multifaceted ontology combines different types of ontologies: the sources ontology defines information sources used by experts for analysis; the domain ontologies describes research interests of the experts needing analysis (they describe ontology of problem including domain ontologies); data formats are described with structures ontology used for structuring data. Multifaceted ontology is the information kernel of the analysis system. Researchers need tools for effective storing and processing information. An approach based on natural language addressing is proposed as perspective method of multifaceted ontology storing. Data structures and algorithms are described and discussed.

Language: English
Full text
DOI
Keywords: multifaceted ontologynatural language addressingdata extractiondata structuring
Publication based on the results of:
Automated Detection of Writing Inaccuracies for Students of English in Russia (2019)

In book

The 13th IEEE International Conference on Application of Information and Communication Technologies (AICT2019): / Conference Proceedings
The 13th IEEE International Conference on Application of Information and Communication Technologies (AICT2019): / Conference Proceedings
Baku: The Institute of Electrical and Electronics Engineering, Inc., 2019.
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