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Author

I. Vergunova

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Conference Sep 2026

Aggregating Duplicate Edges in Text-Derived Knowledge Graphs

Large language models augmented with external knowledge produce more factual and context-rich answers. We present a domain-agnostic framework that transforms unstructured textual evidence into a consolidated knowledge graph, in which nodes are concepts with metadata and edges are statements with structured attributes....

Illia Dagil, I. Vergunova · 0 citations
Conference Sep 2026

Cross-Domain Adaptive Transformer Framework for Robust Object Tracking in Unconstrained Multi-Domain Environments

Visual object tracking (VOT) in real-world scenarios necessitates a high degree of adaptability to overcome the distributions discrepancies inherent in multi-domain environments. While standard deep learning models excel in well-conditioned laboratory datasets, their performance typically degrades when encountering adv...

Volodymyr Husiev, I. Vergunova · 0 citations
Conference Jul 2026

Automated Discovery of Spatio-Temporal Epidemic Patterns via Hybrid Evolutionary-PDE Frameworks

We introduce a hybrid computational framework for the automated discovery of complex dynamic regimes in spatially distributed epidemiological models. Traditional models often fail to capture the rich spatio-temporal heterogeneity of disease spread, while high-dimensional Partial Differential Equation (PDE) models suffe...

Olha Sirikova, I. Vergunova · 0 citations

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