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Big Data Analytics Approach with Multiple Text Types: The Case of the Computer Gaming
P. 275–287.
Aleksandr Belov, Zakharov F., Litvinenko E., Molokanov R., Malyshkina K., Ilya Semichasnov, Markin A.
In book
Vol. 1228. , Springer Publishing Company, 2025.
Aleksei Samarin, Aleksei Toropov, Dzestelova A. et al., , in: Proceedings of the 35th Conference of Open Innovations Association FRUCTVol. 35.: FRUCT Oy, 2024. P. 659–664.
This research endeavor is dedicated to the integration of specialized attentional mechanisms within the intricate web of deep neural network architectures aimed at discerning indications of lung carcinoma from monochromatic snapshots derived from computerized axial tomography. Within this exploration, we propose a myriad of adaptations to the traditional non-local blocks, infusing them with bespoke attentional ...
Added: September 19, 2026
Wind Turbines Surface Damage Automatic Detection Using YOLOv8 with Specialized Backbone Modification
Aleksei Samarin, Mamaeva A., Aleksei Toropov et al., , in: Proceedings of the 36th Conference of Open Innovations Association FRUCTVol. 36.: FRUCT Oy, 2024. P. 702–710.
This work is devoted to incorporating specialized self-attention blocks into deep neural network-based models for detecting and quantifying damage across various components of wind turbines using images captured by unmanned aerial vehicle cameras. In our study, we introduce YOLOv8 backbone modification using a specialized self-attention mechanism, tailored to the specific characteristics of the input data. ...
Added: September 19, 2026
Shavrina T., Fenogenova A., Emelyanov A. et al., , in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).: Association for Computational Linguistics, 2020. P. 4717–4726.
In this paper, we introduce an advanced Russian general language understanding evaluation benchmark – RussianSuperGLUE. Recent advances in the field of universal language models and transformers require the development of a methodology for their broad diagnostics and testing for general intellectual skills - detection of natural language inference, commonsense reasoning, ability to perform simple logical ...
Added: June 14, 2026
Zmitrovich D., Abramov A., Kalmykov A. et al., , in: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024).: ELRA and ICCL, 2024.
Transformer language models (LMs) are fundamental to NLP research methodologies and applications in various languages. However, developing such models specifically for the Russian language has received little attention. This paper introduces a collection of 13 Russian Transformer LMs, which spans encoder (ruBERT, ruRoBERTa, ruELECTRA), decoder (ruGPT-3), and encoder-decoder (ruT5, FRED-T5) architectures. We provide a report ...
Added: June 14, 2026
Biryukova K., Chelnokova D., Erkenova J. et al., , in: Analysis of Images, Social Networks and Texts. AIST 2024Issue 2364.: Cham: Springer, 2024. P. 109–121.
Visual Question Answering is one of the essential parts of machine reasoning. Datasets are created to train a model to perform this task. However, there are only a few datasets for the Russian language. Moreover, existing sets may have strong biases, allowing models to score high without reasoning. In this paper, we adapt the idea ...
Added: June 14, 2026
Chervyakov A., Isaeva U., Emelyanov A. et al., , in: Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)Vol. 1.: Association for Computational Linguistics, 2026. P. 2114–2161.
Multimodal large language models (MLLMs) are currently at the center of research attention, showing rapid progress in scale and capabilities, yet their intelligence, limitations, and risks remain insufficiently understood. To address these issues, particularly in the context of the Russian language, where no multimodal benchmarks currently exist, we introduce MERA Multi, an open multimodal evaluation ...
Added: June 14, 2026
Association for Computational Linguistics, 2026.
Added: June 14, 2026
Chernogorskii F., Averkiev S., Kudraleeva L. et al., , in: Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 4: Student Research Workshop)Vol. 4.: Association for Computational Linguistics, 2026. P. 622–638.
This paper introduces DRAGOn, method to design a RAG benchmark on a regularly updated corpus. It features recent reference datasets, a question generation framework, an automatic evaluation pipeline, and a public leaderboard. Specified reference datasets allow for uniform comparison of RAG systems, while newly generated dataset versions mitigate data leakage and ensure that all models ...
Added: June 13, 2026
Kenneth E., Chung I., Kerboua I. et al., , in: Proceedings of the 13th International Conference on Learning Representations (ICLR 2025).: ICLR, 2025. P. 102004–102060.
Text embeddings are typically evaluated on a limited set of tasks, which are constrained by language, domain, and task diversity. To address these limitations and provide a more comprehensive evaluation, we introduce the Massive Multilingual Text Embedding Benchmark (MMTEB) - a large-scale, community-driven expansion of MTEB, covering over 500 quality-controlled evaluation tasks across 250+ languages. ...
Added: June 11, 2026
Снегирев А., Tikhonova M., Maksimova A. et al., , in: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language TechnologiesVol. 1: Volume 1: Long Papers.: Association for Computational Linguistics, 2025. P. 236–254.
Embedding models play a crucial role in Natural Language Processing (NLP) by creating text embeddings used in various tasks such as information retrieval and assessing semantic text similarity. This paper focuses on research related to embedding models in the Russian language. It introduces a new Russian-focused embedding model called ru-en-RoSBERTa and the ruMTEB benchmark, the ...
Added: June 11, 2026
Churin I., Apishev M., Tikhonova M. et al., , in: Proceedings of the 6th Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences (CODI 2025).: Suzhou: Association for Computational Linguistics, 2025. P. 1–13.
Recent progress in Natural Language Processing (NLP) has driven the creation of Large Language Models (LLMs) capable of tackling a vast range of tasks. A critical property of these models is their ability to handle large documents and process long token sequences, which has fostered the need for a robust evaluation methodology for long-text scenarios. ...
Added: June 11, 2026
Strube M., Braud C., Hardmeier C. et al., Suzhou: Association for Computational Linguistics, 2025.
Added: June 11, 2026
Rabat: Association for Computational Linguistics, 2026.
Added: May 19, 2026
Маленко Маро Янович, Галактика медиа: журнал медиа исследований 2025 Т. 7 № 2 С. 187–208
The article focuses on "ethnological video games", defined as video games which are developed on the basis of ethnographic and folkloric material. The particular focus is on the kind of ethnological games which contain representation or simulation of shamanistic practices. Among them are "Mooseman" based on Komi-Permyak and Finno-Ugric mythology, "Never Alone" based on Iñupiaq ...
Added: May 4, 2026
Мулина А. А., В кн.: Балканские войны 1912–1913 гг.: далекие предпосылки и долгое эхо.: М.: Институт славяноведения РАН, 2024. С. 287–297.
В данной статье рассматривается вопрос отражения событий 1912–1913 гг. в национальных СМИ Сербии в 2012–2013 и 2022–2023 гг. Опираясь на «большие данные», полученные из сервиса Google, а также на материалы качественной газеты «Политика», автор анализирует особенности освещения эпизодов Балканских войн, а также запросы пользователей интернета на территории Сербии по темам, связанным с событиями 1912–1913 гг. ...
Added: April 21, 2026
Мулина А. А., Якова Т. С., Вестник Российского университета дружбы народов. Серия: Литературоведение, журналистика 2025 Т. 30 № 1 С. 161–171
The article presents the results of a study of the information space of the Balkan states conducted during the presidential elections in Turkey (2023): the authors referred to this period as one of the most striking political events in the country over the past five years. The purpose of the proposed work is to identify ...
Added: April 21, 2026
Alexander Demidovskij, Artyom Tugaryov, Igor Salnikov et al., , in: PRICAI 2025: Trends in Artificial Intelligence: 22nd Pacific Rim International Conference on Artificial Intelligence, PRICAI 2025, Wellington, New Zealand, November 17–21, 2025, Proceedings, Part IIIVol. 16453.: Springer, 2026. P. 603–612.
The backpropagation method is the predominant method for pre-training and fine-tuning of Large Language models. At the same time, it is considerably demanding in terms of memory and hardware. Therefore, it makes fine-tuning and pre-training very expensive, harmful for the environment due to the large carbon footprint, and raises the blocks for the development of ...
Added: April 21, 2026
Springer, 2026.
This proceedings contain the papers presented at the 22nd Pacific Rim International Conference on Artificial Intelligence (PRICAI), held on November 17–21, 2025 in Wellington, New Zealand. PRICAI 2025 was co-hosted with the 40th International Conference on Image and Vision Computing New Zealand (IVCNZ 2025) and the annual conference of the New Zealand Artificial Intelligence Researchers ...
Added: April 21, 2026
Momotenko D., Цепелевич М., Ткаченко И. et al., Психология. Психофизиология 2025 Т. 18 № 2 С. 34–46
Introduction. Video games constitute a special form of digital media characterized by dynamic environments that respond to players’ actions and integrated algorithms. Within psychological research, video games offer better validity compared to traditional automated assessment systems, enabling a naturalistic investigation of various phenomena. Furthermore, video games shape mental processes. These features are widely exploited in international psychological research and are critical ...
Added: April 17, 2026
Balayan A. A., Томин Л. В., Публичная политика 2023 Т. 7 № 1-2 С. 108–117
The paper is devoted to the study of certain aspects of the digitalization of public administration in autocracies, primarily government platforms and digital services. The analysis of the political effects of government platforms and services is carried out in the broader context of the study of new cybernetic mode of governance that complement/transform the disciplinary ...
Added: March 31, 2026
Smirnov A., Мониторинг общественного мнения: Экономические и социальные перемены 2021 № 1 С. 129–153
The article considers a theoretical model of digital society based on four concepts: super-connectivity, platformisation, datafication, and algorithmic governance. The model describes how the digitalisation of society deepens: from the transfer of individual practices and social interactions to a new social order based on big data. Analysis of panel data from the 2003–2018 longitudinal survey ...
Added: March 18, 2026
Smirnov A., Экономика региона 2022 Т. 18 № 1 С. 133–145
The nature and intensity of migration processes are constantly changing. Demographic statistics are not suitable for obtaining up-to-date information and making timely decisions in the field of demographic and social policy. Thus, digital demography is becoming increasingly important, as this area of population research uses new methods and data sources resulting from the Internet expansion ...
Added: March 18, 2026
Yalcin H., Demirhan D., Aracioglu B. et al., Technology in Society 2026 Vol. 84 Article 103094
This article comprehensively evaluates the critical role of FinTech in promoting carbon neutrality and green logistics practices in global supply chains. In our study, using bibliometric analysis, social network analysis and natural language processing (NLP) methods, we evaluate the potential of FinTech innovations to increase traceability, transparency and efficiency in supply chain processes. In this ...
Added: March 11, 2026