Author

Piotr Szyma'nski

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#machine learning Preprint Oct 2026

From a Large-Scale Teacher to Efficient Multimodal Students for Search Relevance Prediction

This work proposes a framework that bridges the gap in large language models at scale by distilling a high-performing LLM-based relevance judgment system into efficient multimodal student models, and achieves performance close to the teacher system while significantly improving latency, cost, and scalability.

Tomasz Gniazdowski, Mohammadreza Momenifar, Nadia Vase et al. · 0 citations

#machine learning Preprint Open access Oct 2026

LEON: Location Embeddings from OSM Neighborhoods via Hexagonal Graph Masked Autoencoders

Geographic information systems increasingly rely on sophisticated spatial representation learning techniques to extract meaningful patterns from complex geospatial data. This paper introduces LEON, a novel self-supervised framework that adapts Graph Masked Autoencoders (GraphMAE) for geospatial region representation le...

Szymon Sołtysiak, Radosław Małek, Jedrzej Kusnierz et al. · 0 citations