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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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Neurophysiological correlates of automatic integration of voice and gender information during grammatical processing.

Scientific Reports. 2022. Vol. 12. Article 13114.
Maria Alekseeva, Myachykov A., Beatriz Bermudez‑Margaretto, Shtyrov Y.

During verbal communication, interlocutors rely on both linguistic (e.g., words, syntax) and extralinguistic (e.g., voice quality) information. The neural mechanisms of extralinguistic information processing are particularly poorly understood. To address this, we used EEG and recorded eventrelated brain potentials while participants listened to Russian pronoun–verb phrases presented in either male or female voice. Crucially, we manipulated congruency between the grammatical gender signaled by the verbs’ ending and the speakers’ apparent gender. To focus on putative automatic integration of extralinguistic information into syntactic processing and avoid confounds arising from secondary top-down processes, we used passive non-attend auditory presentation with visual distraction and no stimulus-related task. Most expressed neural responses were found at both early (150 ms, ELAN-like) and late (400 ms, N400-like) phrase processing stages. Crucially, both of these brain responses exhibited sensitivity to extralinguistic information and were signifcantly enhanced for phrases whose voice and grammatical gender were incongruent, similar to what is known for ERPs efects related to overt grammatical violations. Our data suggest a high degree of automaticity in processing extralinguistic information during spoken language comprehension which indicates existence of a rapid automatic syntactic integration mechanism sensitive to both linguistic and extralinguistic information.

Research target: Psychology Philology and Linguistics
Language: English
DOI
Text on another site
Keywords: neurolinguisticsнейролингвистикаmorphosyntaxERPморфосинтаксисвызванные потенциалы мозгаextralinguitic featuresэкстралингвистические показатели
Publication based on the results of:
Multimodal study of neural mechanisms of cognition and decision making in normal and pathological brain (2022)
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