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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
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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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TRUST OF THE GENERATION Z IN ARTIFICIAL INTELLIGENCE IN THE ASSESSMENT OF HISTORICAL EVENTS

Relacoes Internacionais no Mundo Atual. 2022. Vol. 1. No. 34. P. 224–243.
Vinichenko M., Galina Yu. Nikiporets-Takigawa, Oseev A., Makushkin S.

ABSTRACT Objective: The article considered the degree of trust of Russian and Slovak students of generation Z (Gen Z) in artificial intelligence (AI) in the assessment of historical events in the conditions of digital society. Methods: The basic empirical methods of the study were a sociological survey and focus group conducted in the context of the COVID 19 pandemic remotely using the resources of the online Google Form and cloud conference platform Zoom. Results: The study found that the attitude of Gen Z to AI in the context of digitalization of society is ambiguous and contradictory, which affects the degree of trust in the assessment of historical events. The degree of trust of Russian and Slovak Gen Z students in the general issues of the use of AI, the assessment of historical events by AI generally coincide on fundamental issues and have some contradictions on secondary ones. Conclusion: The analysis of the research data showed that Russian and Slovak Gen Z students have a generally positive attitude to historical information coming from AI. Differences in the degree of trust (not trust) between Russian and Slovak Gen Z students in the presentation of historical information to them by the AI, contradiction in the evaluation of individual historical events were revealed. Gen Z is wary of AI, believing that TRUST OF THE GENERATION Z IN ARTIFICIAL INTELLIGENCE IN THE ASSESSMENT OF HISTORICAL EVENTS Revista Relações Internacionais do Mundo Atual Unicuritiba. [Received/Recebido: Fevereiro 15, 2021; Accepted/Aceito Fevereiro 25, 2022] Este obra está licenciado com uma Licença Creative Commons Atribuição-NãoComercial 4.0 Internacional. AI is dangerous for humans and should not be fully trusted in all matters of presentation and assessment of historical events.

Research target: Political Science, International Relations, and Public Administration Sociology (including Demography and Anthropology
Language: English
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Keywords: trustartificial intelligencehistorical eventsdigitalizationgeneration Z
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