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August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Идентификация автора текста в сетевой коммуникации

Вестник Волгоградского государственного университета. Серия 2: Языкознание. 2022. Т. 21. № 3. С. 143–157.
Romanova T. V., Khomenko A.

The article deals with general and particular patterns of solving the identification problem of attributional linguistics on the texts of written network communication. The problem of determining text authorship is solved by comparing a disputed text, the author of which, according to the conditions of the experiment, is unknown, with texts, the authors of which are known. The problem is solved for several discursive areas: online literature, corporate e-mail, short comments on posts on the entertainment portal. These discursive spheres have correlates with several functional styles of speech, fiction, official and colloquial, which makes it possible to identify the trends in textual attribution within the material of Internet communication. For the analysis of speech material, a holistic approach, the tool of which is linguistic modelling, is used. The choice of parameters describing the author’s individual style is rooted to considering text to be a product of an authentic language personality. Language personality is described using psycholinguistic (Yu.N. Karaulov), sociolinguistic and forensic linguistic (S.M. Vul, M. Coulthard, R. W. Shuy) methods. With the help of specialized software "KhoRom", researchers create mathematical models of the individual styles of the compared texts authors. As output the resource displays Pearson correlation coefficient, linear regression and Student’s criterion for the models of the two idiolects represented in compared texts, as well as each parameter metrics values. The software is only a part of the attribution algorithm. The obtained mathematical statistics should be analyzed by experts with the usage of methodological recommendations developed for the algorithm. On the basis of these models and their study, a number of conclusions about statistical patterns of an authorship study in various discursive spheres of electronic communication are made.

Research target: Philology and Linguistics
Language: Russian
Full text
DOI
Keywords: математическая модельязыковая личностьmathematical modelingauthorship attributionлингвистическая модельlinguistic modelсетевая коммуникацияатрибуция текстаlanguage personalitynetwork communication
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