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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.
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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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Application Layer Protocol for a Heterogeneous Group of Mobile Robots in Search and Rescue Scenarios

Lobachevskii Journal of Mathematics. 2025. Vol. 46. No. 4. P. 1879–1891.
Magid E.

Search and rescue (SaR) robotics is a fast-growing domain of academic research and field applications. Robots are widely used in various tasks before, during and after a disaster outbreak. SaR missions require fast hardware deployment, should rely on robust systems and tend employing groups of collaborating robots, which increase overall system performance and reliability. Heterogeneous robotic group connectivity demands a unified way of communication, which could be used by robots with different hardware and software. Such communication protocol should be open source and flexible enough to be applicable in international SaR missions. In this paper, we present a new protocol for heterogeneous robots’ interaction within a SaR mission. The proposed application layer protocol is based on well-tested modern technologies and implements the above-listed features that make it applicable in practice. The protocol is extendable, flexible and outperforms previously developed SaR robotics interaction protocols since it considers advantages, disadvantages and implementation difficulties that had been faced by the previously suggested protocols. The protocol was experimentally validated in a joint mapping task within a laboratory environment.

Research target: Computer Science
Language: English
DOI
Text on another site
Keywords: робототехникаroboticscommunication protocolexperimental validationSearch And Rescueapplication layer protocolпротокол прикладного уровня
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