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Analysis of Images, Social Networks and Texts, 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024, Revised Selected Papers
Vol. 15419.
Springer, 2024.
Academic editor: Panchenko A., D. Gubanov
This book constitutes the refereed proceedings of the 12th International Conference on Analysis of Images, Social Networks and Texts, AIST 2024, held in Bishkek, Kyrgyzstan, during October 17–19, 2024.
The 16 full papers included in this book were carefully reviewed and selected from 70 submissions. They were organized in topical sections as follows: Natural Language Processing; Computer Vision; Data Analysis and Machine Learning; and Theoretical Machine Learning and Optimization.
Chapters
Kudrjashov S., Karpik O., Klyshinskiy E., , in: Analysis of Images, Social Networks and Texts, 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024, Revised Selected PapersVol. 15419.: Springer, 2024. P. 120–130.
Added: May 29, 2025
Sherman K., Ignatov D. I., Tatiana I. Shishkovskaya et al., , in: Analysis of Images, Social Networks and Texts, 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024, Revised Selected PapersVol. 15419.: Springer, 2024. P. 94–108.
More than 3% of people worldwide experience depression. This diagnosis is established through interviews and clinical observations, which is a time- and money-demanding process. Additionally, there are a variety of symptoms associated with depression that are difficult to capture due to the limited capabilities of a human being. Many studies propose methods of automatic mental ...
Added: January 23, 2026
Лукьяненко Д. В., Ragimova A., Мухорина А. et al., European Physical Journal: Special Topics 2026 P. 1–24
Electronic health records (EHRs) contain vast volumes of clinical information that encode complex relationships between diseases. Traditional approaches to the analysis of interrelated or co-occurring diseases have focused on pairwise associations between diagnoses, missing the higher-order structures that characterise multimorbid patients. The present paper offers a narrative review of existing statistical, machine-learning, and artificial intelligence ...
Added: August 20, 2026
CEUR-WS.org, 2026.
The second edition of the Generative Code Intelligence Workshop (GeCoIn 2026) was held in conjunction with the 35th International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2026), in Bremen, Germany, August 16, 2026. The workshop arose from the desire to bring together a research community that has, in recent years, witnessed rapid progress in the application ...
Added: August 20, 2026
Ryumina E., Aksenov A., Koryakovskaya D. et al., IEEE Access 2026 Vol. 14 P. 124759–124778
Psychological characteristic estimation from multimodal in-the-wild behavior is usually studied using separate corpora, each annotated for a single target task. Such annotation fragmentation limits cross-task learning and cross-domain generalization across affective, dispositional, and interactional phenomena. To address this problem, we use emotion, apparent personality trait, and ambivalence recognition as representative tasks and introduce MM-PSYCHE, a ...
Added: August 20, 2026
Association for Computational Linguistics, 2026.
19th Conference of the European Chapter of the Association for Computational Linguistics, Workshop on Linguistic Analysis for Health (2026) ...
Added: August 19, 2026
Vlasenko D., Saranskaia I., Zakharov D., European Physical Journal: Special Topics 2026 P. 1–16
Hypergraphs provide a natural framework for representing neurophysiological interactions distributed across sets of sensors. A key methodological question is how hyperedges should be defined from frequency-resolved electroencephalography/magnetoencephalography (EEG/MEG) data. We demonstrate a construction strategy in which hyperedges are obtained from canonical coherence (caCOH), an extension of coherence that estimates coupling between multidimensional signal spaces. To ...
Added: August 18, 2026
Moshkin A., Fedorov M., Arlazarov V. et al., Algorithms 2026 Vol. 19 No. 7 Article 523
Artificial intelligence (AI) technologies, which are being actively developed in modern medicine today, increase the speed and quality of patient care. This article mainly seeks to demonstrate the use of various options of computer analysis of clinical images to solve practical problems of increasing the efficiency of routine diagnostics using retrospective analysis, as well as ...
Added: August 17, 2026
CHEN Y., Howlett R. J., Tanaka S. et al., Springer, 2026.
The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible ...
Added: August 16, 2026
Khorunzheva K., Postnikov E., Zakharov D., Chaos, Solitons and Fractals 2026 Vol. 212 No. 2 P. 1–12
Identification of coherent states of spiking neural networks is a fundamental problem of
synchronization theory but conventional methods are computationally expensive. We apply
the crystallographic ideas of processing periodic structures to the analysis of various
states of spiking neuronal networks. In particular, the introduced approach is based on
the application of two-dimensional Fourier transform to rasterplots. By the position ...
Added: August 13, 2026
Yu Z., Wang J., Wang Z. et al., Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2026 Vol. 384 P. 1–16
The integration of data-driven and knowledge-driven approaches in generative geospatial modelling (GGM) is often hindered by their mathematical incompatibilities. Here, we propose a geometric algebra (GA)-based framework that employs a unified multi-vector representation to fuse heterogeneous data and diverse knowledge. The framework facilitates structured reasoning and hypothesis generation through a task-adaptable, five-stage cycle: representation, reasoning, ...
Added: August 13, 2026
Cham: Springer, 2026.
This book constitutes the proceedings of the 10th International Workshop Empowering Novel Geometric Algebra for Graphics and Engineering, ENGAGE 2025, held in conjunction with Computer Graphics International conference, CGI 2025, in Hong Kong, China, on July 14, 2025.
The 14 full papers included in this volume were carefully reviewed and selected from 16 submissions. The papers ...
Added: August 13, 2026
Ratnikov F., European Physical Journal: Special Topics 2026 P. 1–10
EEG recordings are often affected by the loss or corruption of individual channels due to electrode detachment, poor scalp contact, or external interference. Such channels must be accurately reconstructed before further analysis. In this study, we investigate Next-Generation Reservoir Computing (NG-RC) as a data-driven approach for reconstructing corrupted EEG channels and compare its performance with ...
Added: August 12, 2026
Minets M., Krasnozhenov G., Trofimova E. et al., PeerJ Computer Science 2026 Vol. 12 Article e4063
This article presents CAD2TechSpec, a novel framework for automating design processes within computer-aided design (CAD) systems by leveraging multimodal large language models (LLMs). The framework enables the analysis and generation of detailed design specifications, including the automated creation of machining process plans. Our system architecture combines 3D model rendering, dimensionality reduction techniques, and the capabilities ...
Added: August 12, 2026
Мизинов П. В., Journal of Computer Virology and Hacking Techniques 2023 No. 20 P. 383–396
Biometric vein recognition systems are vulnerable to presentation attacks. Traditionally, researchers have used a near-infrared (NIR) drawing of the user’s vascular bed to create a presentation attack instrument (PAI). This paper investigates the feasibility of using free software to capture a venous pattern of the hand without NIR under normal lighting conditions and to create ...
Added: August 11, 2026
Trubochkina N. K., М.: Издательство «Юрайт», 2026.
This textbook is designed to develop students' holistic understanding of modern production processes and methods for their analysis and management using machine learning technologies. In the context of the fourth industrial revolution, where traditional engineering disciplines are inextricably intertwined with intelligent data processing methods, there is a growing need for specialists capable of integrating knowledge ...
Added: August 8, 2026
Фирсанова В. И., ACM, 2026.
The inclusion of autistic people can be augmented by a mobile app that provides information without a human mediator making information perception more liberating for people in the spectrum. This paper is an overview of a doctoral work dedicated to the development of a web-based mobile tool for supporting the inclusion of people on the ...
Added: August 4, 2026
Фирсанова В. И., Хлусова Я. К., CEUR Workshop Proceedings, 2025.
Knowledge graphs are widely used in Retrieval Augmented Generation (RAG) and Explainable AI (XAI), since they can illustrate semantic relationships generated by Large Language Models (LLMs). Recent studies focus on generating knowledge graphs from unstructured data to improve RAG performance; however, they do not explain the underlying graph structure. The analysis of synthetic graphs behind ...
Added: August 4, 2026
Belomestny D., Gasnikov A., Gladin E. et al., Russian Mathematical Surveys 2026 Vol. 81 No. 4(490) P. 3–90
Reinforcement learning (RL) is increasingly grounded in tools from probability, optimization, and operator theory. This survey organizes the mathematical structures that underpin the design and analysis of modern algorithms in RL. We begin from Markov decision processes (MDPs) and the Bellman operators, emphasizing contraction mappings, monotonicity, and fixed-point theory that yield convergence guarantees and rates ...
Added: August 3, 2026
Chepovskiy A., М.: Мастерская Печати Идей, 2026.
The textbook presents methods and algoгithms for automatic analysis
of соrроrа of texts in natural languages. It is intended fоr sfudenБ of
methods of processing texts in паtчrаl languages and creating training
arays of texts.
Fоr students, graduate students and researchers studying methods
of computational linguistics and word processing. ...
Added: August 1, 2026
Ponomarenko A., / Series Computer Science "arxiv.org". 2025.
This paper addresses the challenge of merging hierarchical navigable small world (HNSW) graphs, a critical operation for distributed systems, incremental indexing, and database compaction. We propose three algorithms for this task: Naive Graph Merge (NGM), Intra Graph Traversal Merge (IGTM), and Cross Graph Traversal Merge (CGTM). These algorithms differ in their approach to vertex selection ...
Added: July 30, 2026
Уилкокс П., Romanov A., М.: ДМК Пресс, 2025.
Книга, которую вы держите в руках, продолжает серию «Книжная полка истового
инженера», которая издается при поддержке компании YADRO.
Данная книга представляет собой учебник по теоретическим основам продвинутой
функциональной верификации и содержит лучшие практики, используемые в настоящее
время. В ней подробно описана унифицированная методология верификации
(UVM) и раскрыты такие темы, как функциональный виртуальный прототип, функциональное
покрытие, утверждения, формальная верификация, тестбенчи, косимуляция,
эмуляция, аппаратное ...
Added: July 30, 2026
Mikhaylets E. V., Razorenova A. М., Chernyshev V. L. et al., Scientific Reports 2026 Vol. 16 Article 23560
Meditation offers a naturalistic paradigm for studying introspection, yet the neural dynamics of advanced tantric practices remain largely unexplored. Buddhist Highest Yoga Tantra (BHYT) comprises a sequence of eight dissolution stages culminating in the “clear light” state. We recorded EEG during eyes-closed BHYT meditation performed in monasteries and hermitages (51 sessions from 36 male practitioners; ...
Added: July 29, 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