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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 III
Vol. 16453.
Springer, 2026.
Academic editor: M. Yi, Q. Chao, B. Quan, X. Bing, K. Sankalp
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 Association (AIRA 2025). Established in Tokyo in 1990, PRICAI began as a biennial forum dedicated to advancing AI theory, technology, and applications with societal and economic relevance to Pacific Rim countries. Since its inception, the conference has provided a unified platform for researchers and practitioners across diverse AI domains to exchange ideas, discuss emerging trends, and foster cross-disciplinary collaboration. Over the past three decades, PRICAI has expanded substantially in both scope and participation, and since 2019 it has been held annually. It is now recognized as a leading international AI conference serving both the Pacific Rim region and the global AI community.
Chapters
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
Slivnitsin P., Mylnikov L., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
Mokienko O., Zisman M. A., Bobrov P. et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563
Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...
Added: May 28, 2026
М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.
В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...
Added: May 27, 2026
Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6
This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to
implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained)
weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
Added: May 26, 2026
Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94
В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118
This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...
Added: May 22, 2026
Jin S., Komarov M. M., Scientific Reports 2026
Intrabody communication (IBC) channels offer physiological diversity that can be leveraged for passive biometric identification in wearable devices. Recent reports of over 99 per cent identification accuracy have frequently resulted from data leakage, where samples from the same subject are seen in both training and evaluation, yielding inflated and unreliable metrics. In this work, we ...
Added: May 21, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Rabat: Association for Computational Linguistics, 2026.
Added: May 19, 2026
Malikov D., Krasnov L., Kiseleva M. et al., Scientific data 2026 Vol. 13 Article 727
Solubility is a crucial property of organic compounds, impacting their potential applications in synthetic chemistry, materials science and drug design. Moreover, in technological processes mixtures of solvents are often utilized, making the solubility assessment more complicated. Predicting solubility values in mixtures of solvents from a molecular structure can help to address this issue, although a ...
Added: May 19, 2026
Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69
This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...
Added: May 19, 2026
Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69
This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...
Added: May 19, 2026
Springer, 2025.
This book constitutes the refereed proceedings of the 19th International Conference on Parallel Computational Technologies, PCT 2025, held in Moscow, Russia, during April 8–10, 2025.
The 31 full papers included in this volume were carefully reviewed and selected from 122 submissions. These papers were organized under the following topical sections: High Performance Architectures, Tools and Technologies; ...
Added: May 18, 2026
Ronglin Z., Wei L., Jiahong C. et al., Journal of Signal Processing Systems 2026 Vol. 98 Article 31
To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key ...
Added: May 16, 2026
Suvorov N. M., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3(2) P. 49–66
Data Petri Nets (DPNs) extend classical Petri nets to model processes where data directly influences control-flow, enabling a comprehensive view of system behavior and possibility to detect failure points that could otherwise be hidden. Soundness is a correctness criterion that captures such failure points as deadlocks and livelocks as well as model boundedness and absence ...
Added: May 16, 2026
Радушев Д. О., Dogonasheva O., Гуткин Б. С. et al., Chaos 2026 Vol. 36 No. 5 P. 1–10
In recent decades, analysis of dynamic states in neural networks has become an important direction of the synchronization theory. One of the most interesting neuronal network states is the chimera state, in which coherent and incoherent activity clusters coexist. While chimera states have been shown to exist in various networks, their precise automatic identification in ...
Added: May 13, 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
СПб.: Санкт-Петербургский Федеральный исследовательский центр РАН, 2025.
Двадцать вторая Национальная конференция по искусственному интеллекту с международным участием КИИ-2025 продолжает традицию советских (российских) конференций, организуемых Российской ассоциацией искусственного интеллекта. Во втором томе трудов публикуются доклады участников конференции, представленные на следующих секциях: Секция 5 «Нечеткие модели, мягкие измерения и вычисления, биоинспирированные методы», Секция 6 «Интеллектуальные агенты, роботы, компьютерное зрение», Секция 7 «Интеллектуальное управление и ...
Added: March 3, 2026
Bernadotte A, Elfimov N., Menshikov I., Scientific data 2025 Vol. 13 No. 41
Accurate segmentation of brain vessels in magnetic resonance angiography (MRA) is essential for surgical procedures. Neural networks are powerful tools for medical image segmentation, but their development requires well-annotated datasets. However, publicly available MRA datasets with detailed vessel annotations are scarce. We present a dataset of 100 manually annotated brain MRA images from the IXI ...
Added: February 25, 2026