VEM$^2$L: A Plug-and-play Framework for Fusing Text and Structure Knowledge on Sparse Knowledge Graph Completion. (arXiv:2207.01528v3 [cs.CL] UPDATED)

Knowledge Graph Completion (KGC) aims to reason over known facts and infer
missing links but achieves weak performances on those sparse Knowledge Graphs
(KGs). Recent works introduce text information as auxiliary features or apply
graph densification to alleviate this challenge, but suffer from problems of
ineffectively incorporating structure features and injecting noisy triples. In
this paper, we solve the sparse KGC from these two motivations simultaneously
and handle their respective drawbacks further, and propose a plug-and-play
unified framework VEM$^2$L over …

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