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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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Monolingual and Bilingual Reading Processes in Russian: An Exploratory Scanpath Analysis

Reading Research Quarterly. 2022. Vol. 57. No. 2. P. 469–492.
Parshina O., Sekerina I. A., Lopukhina A., von der Malsburg T.

In the present study, we used a scanpath approach to investigate reading processes and factors that can shape them in monolingual Russian-speaking adults, 8-year-old children, and bilingual Russian-speaking readers. We found that monolingual adults’ eye movement patterns exhibited a fluent scanpath reading process, representing effortless processing of the written material: They read straight from left to right at a fast pace, skipped words, and regressed rarely. Both high-proficiency heritage-language speakers’ and second graders’ eye movement patterns exhibited an intermediate scanpath reading process, characterized by a slower pace, longer fixations, an absence of word skipping, and short regressive saccades. Second-language learners and low-proficiency heritage-language speakers exhibited a beginner reading process that involved the slowest pace, even longer fixations, no word skipping, and frequent rereading of the whole sentence and of particular words. We suggest that unlike intermediate readers who use the respective process to resolve local processing difficulties (e.g., word recognition failure), beginner readers, in addition, experience global-level challenges in semantic and morphosyntactic information integration. Proficiency in Russian for heritage-language speakers and comprehension scores for second-language learners were the only individual difference factors predictive of the scanpath reading process adopted by bilingual speakers. Overall, the scanpath analysis revealed qualitative differences in scanpath reading processes among various groups of readers and thus adds a qualitative dimension to the conventional quantitative evaluation of word-level eye-tracking measures.

Research target: Philology and Linguistics Psychology
Priority areas: humanitarian
Language: English
DOI
Text on another site
Keywords: Russian languageheritage speakersdeveloping reading skillseye tracking data analysisL2 learnersscanpaths
Publication based on the results of:
Язык и мозг: предотвращение, диагностика и коррекция речевых расстройств (2020)
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