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News
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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Proceedings of the 10th Workshop on Slavic Natural Language Processing (Slavic NLP 2025)

Association for Computational Linguistics, 2025.
Academic editor: J. Piskorski, P. Přibáň, P. Nakov, R. Yangarber, M. Marcinczuk
Chapters
Rubic2: Ensemble Model for Russian Lemmatization
Afanasev I., Glazkova A., Lyashevskaya O. et al., , in: Proceedings of the 10th Workshop on Slavic Natural Language Processing (Slavic NLP 2025).: Association for Computational Linguistics, 2025. P. 157–170.
Pre-trained language models have significantly advanced natural language processing (NLP), particularly in analyzing languages with complex morphological structures. This study addresses lemmatization for the Russian language, the errors in which can critically affect the performance of information retrieval, question answering, and other tasks. We present the results of experiments on generative lemmatization using pre-trained language ...
Added: March 10, 2026
Research target: Computer Science Philology and Linguistics
Language: English
Text on another site
Keywords: Slavic languagesNatural Language and Speech natural language processing
Proceedings of the 10th Workshop on Slavic Natural Language Processing (Slavic NLP 2025)
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An adaptive image watermarking scheme using cooperation of HBA and RSA metaheuristics
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Added: August 25, 2026
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Proceedings of the 2026 12th International Conference on Control, Decision and Information Technologies (CoDIT) (Italy, Bari, July 13–16, 2026)
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Added: March 10, 2026
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