most citedVL-KGE: Vision-Language Models Meet Knowledge Graph Embeddings

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cs.AI2026

Discrete Diffusion for Large Graph Generation via Structural Candidate Restriction

Yassin Mohamadi, Zeno Geradts, Marcel Worring

Synthesizing realistic graphs at scale is vital when the graphs of interest are large and real-world samples are limited or access-sensitive. Diffusion-based generators have recent…

cs.AI2026★ 1 cited

VL-KGE: Vision-Language Models Meet Knowledge Graph Embeddings

Athanasios Efthymiou, Stevan Rudinac, Monika Kackovic +2

Real-world multimodal knowledge graphs (MKGs) are inherently heterogeneous, modeling entities that are associated with diverse modalities. Traditional knowledge graph embedding (KG…