Multimodal verification systems may assign high confidence to misleading claims when an associated image is visually plausible but does not provide valid evidence. This paper introduces TrustLift, a lightweight framework for detecting such false-reassurance errors and selectively referring risky cases for review. The m...
Alexey S. Borodulin, I. Masich, V. Tynchenko et al.· 0 citations
Short-term electricity load forecasting is a key task for smart-grid operation, industrial energy management, and predictive planning. This paper presents a reproducible comparative study of classical, machine-learning, deep-learning, and foundation-model approaches for hourly load forecasting. The benchmark includes S...
А. М. Князев, N. Grechanikov, V. Tynchenko· 2026 International Russian A...· 0 citations
Adaptive algorithmic methods are essential for intelligent control systems in modern power grids and electrotechnical complexes, enabling real-time optimization, fault tolerance, and operational stability under varying conditions. This paper presents a comparative study of two adaptive control approaches-Reinforcement...
S. Shiryaeva, V. Tynchenko, K. Muzalev· 2026 International Russian A...· 0 citations
The transition toward unmanned and hybrid vessels increases the requirements for diagnosability and continuity of power supply to critical consumers under physical and information-layer faults. The aim of this study is to develop a probabilistic digital twin of a shipboard microgrid that combines nonlinear state estima...
S. Kondratyev, E. V. Khekert, N. Martyushev et al.· Energies· 0 citations
VeriCrypt-Agent is presented, an evidence-grounded workflow for bounded-autonomy cryptographic maintenance that combines a frozen snapshot of release/advisory evidence, a public catalog of project-level executable probes, cross-version execution under old and candidate dependency versions, role-specialized LLM reasonin...
V. Tynchenko, Alexey S. Borodulin, Dmitriy Martysyuk et al.· Computers· 0 citations
Deep hypergraph learning is evaluated almost entirely through leaderboards that rank methods by mean accuracy over a few random seeds, usually without significance testing. Is there a best hypergraph neural network, or does the apparent ordering reflect seed noise? We independently recomputed the node-classification tr...
V. Tynchenko, S. Kurashkin, Alexey S. Borodulin et al.· Machine Learning and Knowled...· 0 citations
Spent water-based drilling fluids generated during the construction of technological wells impose substantial environmental, water-management, transportation, and energy burdens. Conventional practices, including storage in temporary pits, prolonged settling, and off-site disposal, do not enable process-water recovery...
B. Mauletbekova, B. Kaliyev, B. Myrzakhmetov et al.· Applied Sciences· 1 citation
This review is, to the authors' knowledge, the first organised around the current generation of tabular foundation models, and taxonomises the architectures by pretraining regime, maps the capability space across five axes, isolates the language-model-on-tabular strand for prediction, feature engineering and generation...
S. Kurashkin, V. Tynchenko, Alexey S. Borodulin et al.· Machine Learning and Knowled...· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
