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This paper introduces a novel prototype-enhanced hypergraph learning approach for node classification in HINs using hypergraphs instead of graphs, which captures higher-order relationships among nodes and extracts semantic information without relying on metapaths.
MMArt is introduced, a large-scale dataset of 74,234 WikiArt paintings, each annotated with four independently annotated perspectives plus a harmonized unified caption, produced by specialized vision-language models or human annotation and validated through complementary quality evaluations.
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