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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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Neurophysiological evidence of single-shot semantic mapping in the developing brain

Frontiers in Human Neuroscience. 2025. Vol. 19. Article 1533833.
Vasilyeva M., Knyazeva V., Elena D. Artemenko, Vershinina E., Garbaruk E., Boboshko M., Aleksandrov A., Shtyrov Y.

Rapid acquisition of new words and construction of large vocabularies is a unique capacity of developing human brain. This process is to a large degree mediated by a neurocognitive mechanism known as «fast mapping» (FM) which allows the child to quickly map new words onto neural representations after even a single exposure to them, using context-driven inference. However, the neurophysiological bases of this mechanism are still poorly understood. To address this open question, we used event-related potentials (ERPs) to investigate brain dynamics elicited by novel words following a single-shot audiovisual semantic learning task and to estimate cortical underpinnings of this process in healthy preschool children. We found that a single presentation of novel words in association with novel objects leads to a decrease in the brain’s activation, registered as an early N400 effect for newly learnt word forms, indicating rapid lexicosemantic memory trace formation in the developing brain. Interestingly, source analysis indicated this effect to be chiefly underpinned by activity modulations in the right-hemispheric temporal cortices, indicating their involvement in speech processing at an early age (known to be diminished later in life). Overall, current findings provide the electrophysiological evidence of the specific mechanism in the developing brain that promotes rapid integration of novel word representations into neocortical lexicosemantic networks after a single exposure, subserving efficient native word acquisition and mastering the mother tongue.

Research target: Biology Psychology
Language: English
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Keywords: EEGpreschool childrenERPNovel word learningfast mapping (FM)
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