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Formal Concept Analysis for Evaluating Intrinsic Dimension of a Natural Language
Lecture Notes in Computer Science. 2023. P. 331–339.
Some results of a computational experiment for determining the intrinsic dimension of linguistic varieties for the Bengali and Russian languages are presented. At the same time, both sets of words and sets of bigrams in these languages were considered separately. The method used to solve this problem was based on formal concept analysis algorithms. It was found that the intrinsic dimensions of these languages are significantly less than the dimensions used in popular neural network models in natural language processing.
Калужский печатный двор, 2026.
Conference Proceedings INTERNATIONAL CONFERENCE
“Mathematical Ideas of Academician
P.L. Chebyshev, Their Applications in Natural
Sciences and Artificial Intelligence Technologies”
dedicated to the 205th anniversary of his birth ...
Added: June 20, 2026
Stognieva O., Чеснокова Н. Е., Отечественная и зарубежная педагогика 2026 Т. 1 № 3 (115) С. 123–131
Integration of generative artificial intelligence tools into educational practice highlights the need for pedagogically grounded approaches to their use in the creation of educational video content, which is increasingly applied in language and professionally oriented instruction.
The purpose of this article is to conduct a comparative analysis of educational video content created using generative AI tools ...
Added: June 20, 2026
Cherednichenko O., Herbert A., Poptsova M., Computational and Structural Biotechnology Journal 2025 Vol. 27 P. 992–1000
Large language models (LLMs) in genomics have successfully predicted various functional genomic elements. While their performance is typically evaluated using genomic benchmark datasets, it remains unclear which LLM is best suited for specific downstream tasks, particularly for generating whole-genome annotations. Current LLMs in genomics fall into three main categories: transformer-based models, long convolution-based models, and state-space models ...
Added: June 19, 2026
Poptsova M., Briefings in Bioinformatics 2025 Vol. 26 No. 2 P. 1–11
Kolmogorov–Arnold networks (KANs) emerged as a promising alternative for multilayer perceptrons (MLPs) in dense fully connected networks. Multiple attempts have been made to integrate KANs into various deep learning architectures in the domains of computer vision and natural language processing. Integrating KANs into deep learning models for genomic tasks has not been explored. Here, we ...
Added: June 19, 2026
Анненков А. Н., Nesterov R., Моделирование и анализ информационных систем 2026 Т. 33 № 2 С. 176–205
Declarative process models are widely used in process mining to describe flexible process behavior through sets of constraints. However, models discovered automatically from event logs may contain inconsistent constraints, which can make them difficult to interpret and unusable for execution, conformance checking, or further analysis. Existing methods for consistency analysis either rely on automata-based constructions ...
Added: June 18, 2026
Cham: Springer Publishing Company, 2026.
The four-volume set LNCS 16483-16486 constitutes the refereed conference proceedings of the 48th European Conference on Information Retrieval, ECIR 2026, held in Delft, The Netherlands, during March 29–April 2, 2026.
The 46 full papers and 37 short papers presented together with 10 findings papers, 9 reproducibility papers, 17 resource papers, 11 workshop papers, 7 tutorial papers, ...
Added: June 18, 2026
Poddiakov A., Троицкий вариант. Наука 2026 № 12 С. 24–25
В научно-популярной заметке представлен обзор содержания поста филдсовского медалиста Тимоти Гауэрса о возможностях ИИ в математике и содержания комментариев под постом. Обзор сделан в основном чат-ботом DeepSeek. В заключение обсуждается возможность не только решения задач искусственным интеллектом, но и их постановки. ...
Added: June 18, 2026
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
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
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
Makarov N., Savchenko A., Zemtsova I. et al., Scientific Reports 2025 Vol. 15 Article 26641
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
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
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
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
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
Association for Computational Linguistics, 2026.
Added: June 14, 2026
Strube M., Braud C., Hardmeier C. et al., Suzhou: Association for Computational Linguistics, 2025.
Added: June 11, 2026
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
Namsaraev Z., Nanzatov B., Kozlova A. et al., Scientific Reports 2026 Vol. 16 No. 1 Article 17769
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
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
Razzhigaev A., Mikhalchuk M., Goncharova E. et al., , in: Findings of the Association for Computational Linguistics: EACL 2024.: Association for Computational Linguistics, 2024. P. 868–874.
Added: February 17, 2025
Ignatov D. I., Lobachevskii Journal of Mathematics 2023 No. 44 P. 137–146
We consider two ways how to compute the number of maximal antichains in the Boolean lattice on 𝑛 elements. The first one is based on full direct enumeration, while the second ones relies on concept lattices or Galois lattices (studied in Formal Concept Analysis, an applied branch of lattice theory) and the Dedekind–MacNeille completion of a partial ...
Added: June 13, 2023
Parakal E. G., Kuznetsov S., , in: Proceedings of the 10th International Workshop "What can FCA do for Artificial Intelligence?"Vol. 3233.: CEUR Workshop Proceedings, 2022. Ch. 2 P. 9–22.
Explanations for the predictions made by Machine Learning (ML) models are best framed in terms of
abstract, high-level concepts that are easily comprehensible to human beings. The use of such concepts
constitutes a subfield of interpretability methods known as concept-based explanations. This work uses
concept-based explanations to build an intrinsically interpretable document classifier using a combination
of Formal Concept ...
Added: May 17, 2023
Ignatov D. I., Yakovleva A., , in: Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2021)Vol. 2972.: CEUR-WS, 2021. P. 87–98.
In this paper we study certain properties of the GreConD algorithm for Boolean matrix factorisation, a popular technique in Data Mining with binary relational data. This greedy algorithm was inspired by the fact that the optimal number of factors for the Boolean matrix factorisation can be chosen among the formal concepts of the correspond- ing ...
Added: November 1, 2021