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Subject
News
June 19, 2026
HSE Researchers Determine Which Internet Users Are More Likely to Fact-Check
Researchers at HSE University examined the strategies employed by Russian internet users to verify unreliable information and the factors that motivate them to do so. The study found that more than half of users who encounter potentially false information online attempt to verify it by locating the original source. The likelihood of fact-checking is influenced by several factors, including age, place of residence, social status, information literacy skills, and the use of AI. The findings have been published in Monitoring of Public Opinion: Economic and Social Changes.
June 5, 2026
'Im Used to Producing Distilled Knowledge'
Ivan Rubachev works in a HSE University laboratory established jointly with Yandex Research, where he focuses on machine learning with tabular data. In this interview with the HSE Young Scientists project, he discusses why following a vibe can be better than goal-setting, explains the concept of the Neural Turing Machine, and argues why withholding scientific knowledge is counterproductive.
June 17, 2026
Population Lifespan Is Governed by Mathematical Laws
Researchers at HSE University and MSU have established a universal law governing the time to extinction of a population in a random environment. Their analysis of the evolution of branching processes—complex probabilistic systems—shows that, regardless of the initial population size, extinction follows strict mathematical laws. The results have been published in the Journal of Applied Probability.

 

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ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ И ТЕХНИЧЕСКИЕ СРЕДСТВА УПРАВЛЕНИЯ (ICCT-2024)

M. : -, 2024.
Editor-in-chief: Е. А. Барабанова, К. А. Вытовтов
Chapters
CautiousBug path planning algorithm package for ROS Noetic
Roman M., Eryomin A., Tsoy T. et al., , in: ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ И ТЕХНИЧЕСКИЕ СРЕДСТВА УПРАВЛЕНИЯ (ICCT-2024).: М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024. P. 184–186.
The problem of robot navigation in unknown environments can be addressed without using a ready map or constructing a new one. The Bug family algorithms focus on sensor odometry data. The CautiousBug algorithm stands out from the rest of the algorithms by a considerable property: as its name implies, it does not make risky decisions ...
Added: April 22, 2026
Research target: Computer Science
Language: Russian
Full text
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Keywords: информационные технологиитехнические средства управления
ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ И ТЕХНИЧЕСКИЕ СРЕДСТВА УПРАВЛЕНИЯ (ICCT-2024)
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Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation
Beznosikov A., Kormakov G., Grigorievskiy A. et al., Journal of Optimization Theory and Applications 2026 Vol. 209 Article 18
The objective of Vertical Federated Learning (VFL) is to collectively train a model using features available on different devices while sharing the same users. This paper focuses on the saddle point reformulation of the VFL problem via the classical Lagrangian function. We first demonstrate how this formulation can be solved using deterministic methods.More importantly, we explore various stochastic modifications to ...
Added: June 17, 2026
Supervised Learning in Critical Phenomena—Statistical and Systematic Accuracy
Chertenkov V. I., Shchur L., Lobachevskii Journal of Mathematics 2026 Vol. 47 No. 2 P. 720–727
Supervised machine learning is successfully applied to the study of critical phenomena and allows us to obtain a numerical estimate of the phase transition temperature and the correlation length exponent. We discuss the influence of possible systematic errors, as well as statistical errors, on the accuracy of such numerical estimates. Errors in the training and ...
Added: June 16, 2026
Enhancing Emotion Recognition in Speech Based on Self-Supervised Learning: Cross-Attention Fusion of Acoustic and Semantic Features
Deeb B., Andrey V. Savchenko, Makarov I., IEEE Access 2026 Vol. 13 P. 56283–56295
Speech Emotion Recognition has gained considerable attention in speech processing and machine learning due to its potential applications in human-computer interaction, mental health monitoring, and customer service. However, state-of-the-art models for speech emotion recognition use many parameters, which leads to computational complexity. In this paper, we introduce a novel deep-learning model to enhance the accuracy ...
Added: June 16, 2026
Automated detection of wolf howls using audio spectrogram transformers
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The grey wolf (Canis lupus) is a pivotal species for ecological studies. As a key participant in ecosystem processes, it also serves as a model for investigating social structure formation and ecological adaptation. However, the species’ complex social behavior, spatial dynamics, and expansive habitats make monitoring and population assessments across large areas particularly challenging. In recent years, audio traps ...
Added: June 16, 2026
Artificial intelligence framework for multi-pathology risk assessment from retinal fundus images: deep learning approach to 15-disease screening
Vasilev R., Savchenko A., Blinov P. et al., Frontiers in Medicine 2026 Vol. 13
Automated disease screening systems face challenges when applied to multi-class medical image analysis, particularly under severe class imbalance inherent in clinical datasets. Retinal fundus imaging enables non-invasive screening for multiple ocular and systemic diseases simultaneously, yet current automated systems typically assess risk for only a single pathology or a limited disease range. We developed a ...
Added: June 16, 2026
From Data to Signs: A Foundation Model for Multilingual Sign Language Recognition
Novopoltsev M., Tulenkov A., Murtazin R. et al., IEEE Access 2025 Vol. 13 P. 188170–188181
Video-based Isolated Sign Language Recognition (ISLR) problem presents significant challenges in scaling across diverse languages due to data scarcity and the computational costs associated with training of language-specific models. In this paper, we introduce a novel training pipeline that leverages self-supervised learning on a large-scale sign language dataset. To obtain the foundation model, we utilize ...
Added: June 16, 2026
B3Emo: Quantifying Affect as a Double-Edged Sword in Strategic LLM Interactions
Stepin A., Mozikov M., Kabanov A. et al., IEEE Access 2026 Vol. 14 P. 48127–48144
The deployment of large language models (LLMs) in interactive roles such as automated negotiators, customer service agents, and strategic partners requires them to handle not only logical tasks but also the socio-emotional dimensions of interaction. In these situations, success often relies on understanding social cues, building trust, and using persuasion effectively. These skills are closely ...
Added: June 16, 2026
ESQA: Event Sequences Question Answering
Abdullaeva I., Karpukhin I., Filatov A. et al., IEEE Access 2026 Vol. 14 P. 59390–59408
Event sequences, a specialized type of tabular data annotated with timestamps, are prevalent across practical domains such as finance, retail, social networks, and healthcare. Despite the importance of event sequence modeling and analysis, there has been little effort to adapt Large Language Models (LLMs) to this domain. In this paper, we propose a novel solution ...
Added: June 16, 2026
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Association for Computational Linguistics, 2026.
Added: June 14, 2026
Proceedings of the 6th Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences (CODI 2025)
Strube M., Braud C., Hardmeier C. et al., Suzhou: Association for Computational Linguistics, 2025.
Added: June 11, 2026
TreeDQN: Sample-efficient off-policy reinforcement learning for combinatorial optimization
Sorokin D., Kostin A., Savchenko L. et al., Knowledge-Based Systems 2026 Vol. 348 Article 116258
A convenient approach to optimally solving combinatorial optimization tasks is the Branch-and-Bound method. Its branching heuristic can be learned to solve a large set of similar tasks. The promising results here are achieved by the recently appeared on-policy reinforcement learning method based on the tree Markov Decision Process. To overcome its main disadvantages, namely, very large training time ...
Added: June 10, 2026
Microbial diversity and production of milk spirit using traditional Buryat fermentation and distillation technologies
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Distilled fermented milk beverages are rare in food technology, despite the global prevalence of plant-based spirits. Currently, the production of distilled strong alcoholic beverages from fermented milk using traditional technologies is known only among Mongolic-speaking peoples and their Siberian neighbors. This study provides the first interdisciplinary analysis of darasun, a traditional Buryat spirit made from fermented ...
Added: June 10, 2026
Artificial intelligence and digital twins for failure prediction in data center cooling systems: a comprehensive literature review (2018–2026)
Butorova A., Bobakov V., Sergeev A. et al., European Physical Journal: Special Topics 2026 P. 1–19
This paper presents a review of artificial intelligence (AI) methods for failure prediction in data center cooling systems, with a focus on the integration of digital twins (DTs), physics-informed learning, and graph-based models. Positioned within complex network science, this review addresses a limitation of conventional graph approaches—their reliance on pairwise connectivity—whereas real-world failures often arise ...
Added: June 10, 2026
Innovations in Information and Decision Sciences. Proceedings of the 13th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2025), Volume 4
Springer, 2026.
The book presents the proceedings of the 13th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2024), held at Intelligent Systems Research Group (ISRG), London Metropolitan University, London, United Kingdom, during June 6–7, 2025. Researchers, scientists, engineers and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with ...
Added: June 8, 2026
Правовой режим объектов, созданных искусственным интеллектом: обзор зарубежной практики
Kirsanova E., Pakshin P., Право и экономика 2026 № 3 (456) С. 26–34
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Added: April 28, 2026
The Role of Inclusive Leadership in Developing Interpersonal Trust Profiles
Volkova N., Sugianto N., Psychology. Journal of the Higher School of Economics 2026 Vol. 23 No. 1 P. 211–231
Utilizing the transformational approach of trust development and the social information processing theory, this research aims to shed light on the unique employee groups (profiles) identified through their affect- and cognition-based interpersonal trust and the relationships of these profiles with the sense of the inclusive behavior of leaders by contrasting two different countries (i.e., the ...
Added: April 5, 2026
Применение технологий искусственного интеллекта в цифровой публичной дипломатии США: перспективы и возможности для России
Orodvsky D., Дискурс-Пи 2025 Т. 22 № 4 С. 211–223
This article explores the role of artificial intelligence (AI) technologies in the digital public diplomacy of the United States and evaluates their potential relevance for Russian foreign policy strategies. As global communication becomes increasingly data-driven and technology-centric, AI is emerging as a key instrument for shaping narratives, analyzing public opinion, and enhancing the effectiveness of ...
Added: February 6, 2026
ИСПОЛЬЗОВАНИЕ ИНФОРМАЦИОННЫХ ТЕХНОЛОГИЙ ПРИ ВЗАИМОДЕЙСТВИИ ПРОКУРАТУРЫ С ОРГАНАМИ МЕСТНОГО САМОУПРАВЛЕНИЯ
Kramarenko L., Законность 2024 № 3 С. 16–19
Modern society, as well as the prosecutor's office and local self-government bodies, cannot be imagined without information technology. In this regard, the author suggests using information technology in the interaction between the prosecutor's office and local self-government bodies, which, in his opinion, will significantly affect the effectiveness of these bodies. ...
Added: January 21, 2026
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This review synthesizes the functions of external enterprise training conducted by IT companies, targeting non-employee students. Key functions include enhancing employer branding, recruiting talent, promoting high-tech products, and improving the accessibility and quality of IT education. ...
Added: January 18, 2026
Дидактические возможности нейросетей в контексте полимодального обучения иностранным языкам (на примере генерации видеоконтента)
Popova A., Иностранные языки в школе 2025 № 1 С. 76–83
The development of artificial intelligence technologies, and neural networks in particular, is accelerating every day. The process of their integration into foreign language teaching is becoming increasingly obvious to teachers and students. Thanks to the various functions of neural networks, new opportunities for teaching foreign languages are opening up. This article is a continuation of ...
Added: December 20, 2025
Цифровая трансформация экономики: вызовы и проблемы
Русайнс, 2025.
В сборнике излагаются методические подходы к определению цифровой трансформации в экономических и социальных процессах в производственном, аграрном, финансовом секторах и услугах. С этой целью проведены анализы существующей инфраструктуры цифровой среды, цифровых платформ, выявлены различия в уровне и специфике цифрового потребления между жителями российских городов. На основе результатов анализа предложены методические рекомендации по выбору информационных технологий ...
Added: December 20, 2025
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Added: October 13, 2025
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