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News
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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Neural Processing of Social Stimuli in High vs. Low Social Anxiety Individuals: A Pilot Study

Proceedings of the IEEE. 2024.
Alenina E., Терентьева К. С., Kosonogov V.

Social anxiety is characterized by fear in various socially related situations. Research demonstrates that people with high social anxiety have lower self-esteem and experience negative impacts from this state. The current pilot study aimed to investigate neural responses to social stimuli in individuals with high and low social anxiety. Fifty-seven participants completed an online screening form to assess anxiety levels, with four participants selected for each group based on their scores (High Social Anxiety group: M_age = 20.57, SD = 4.27; Low Social Anxiety group: M_age = 28.5, SD = 7.18). Participants underwent EEG recordings while being exposed to facial expression stimuli. Results revealed lower event-related potentials (ERPs) in individuals with high social anxiety compared to those with low social anxiety. These findings suggest altered neural processing of social cues in individuals with high social anxiety, highlighting the need for further investigation into the underlying mechanisms.

Research target: Psychology Biology
Language: English
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Keywords: EEGЭЭГevent related potentialsсоциальная тревожностьsocial anxietyВП (вызванные потенциалы)high social anxietylow social anxietyвысокая социальная тревожностьнизкая социальная тревожность
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