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my name is ke from University of University of Science and Technology of China let me introduce our paper fact in banding through diffusion model for Knowledge Graph competion first Knowledge Graph is a world model it consists of lots of tribet each tribulate has head entities relation and the T entities entities as relations defines our domain of dource but how to encode them is a problem traditional uh method using Knowledge Graph EMB banding models map entities and the relations into Vector space and Define a score score function to capture the connectivities patterns however since these patterns are very complex in the real world it is it is difficult to Define score function to capture them this paper argues that the the fact comes from a distribution in fact space Inspire this inside this paper propos a no framework called the fact in banding through diffusion models fdm to address the KGC test extensive experiment demonstrate fdm output perform the soda method in the KGC task th
