DiffTSP applies discrete diffusion to knowledge graph triple set prediction, recovering all missing triples simultaneously via edge-masking noise reversal and a structure-aware transformer, achieving SOTA on three datasets.
Modeling relational data with graph convolutional networks
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CORE embeds relations as cyclic orthotopes on a torus with adaptive width regularization to enable boundary-less optimization and capture complex logical patterns in knowledge graphs.
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One Pass for All: A Discrete Diffusion Model for Knowledge Graph Triple Set Prediction
DiffTSP applies discrete diffusion to knowledge graph triple set prediction, recovering all missing triples simultaneously via edge-masking noise reversal and a structure-aware transformer, achieving SOTA on three datasets.
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CORE: Cyclic Orthotope Relation Embedding for Knowledge Graph Completion
CORE embeds relations as cyclic orthotopes on a torus with adaptive width regularization to enable boundary-less optimization and capture complex logical patterns in knowledge graphs.