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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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«Подводные камни» биоинспирированных моделей на примере муравьиных дорог

Автоматика и телемеханика. 2024. № 7. С. 113–130.
Karpova I. P., Karpov V. E.

This paper explores the problem of influencing the environment by a group of autonomous robots through the creation and use of road infrastructure. The model object is ant roads (trails). We identify the main aspects of the behavior of different ant species in the process of collective foraging, and actions that together lead to the appearance of a phenomenon that the observer perceives as an ant road. We develop and describe an animat behavior model in the process of arranging a route. We define a list of mechanisms, a set of sensory capabilities, and effectors that are necessary for the robot to implement options for arranging the route. The results of simulation modeling for solving the foraging problem with route clearing are consistent with theoretical models. The simulation results confirm our assumption that the route arrangement can be carried out by individual efforts of animats (robots) and without the need to organize joint actions.

Research target: Computer Science
Language: Russian
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Keywords: модели социального поведениягрупповая робототехникаforaging taskcollective roboticssocial behavior modelsзадача фуражировкиautonomous mobile robotsbio-inspired modelsавтономные мобильные роботыбиоинспирированные модели
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