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cs.CL2026★ 1 cited
jina-embeddings-v5-omni: Geometry-preserving Embeddings via Locked Aligned Towers
Florian Hönicke, Michael Günther, Andreas Koukounas +3
In this work, we introduce GELATO (Geometry-preserving Embeddings via Locked Aligned TOwers), a novel approach to multimodal embedding models. We build on the VLM-style architectur…
cs.CL2026
jina-embeddings-v5-text: Task-Targeted Embedding Distillation
Mohammad Kalim Akram, Saba Sturua, Nastia Havriushenko +4
Text embedding models are widely used for semantic similarity tasks, including information retrieval, clustering, and classification. General-purpose models are typically trained w…