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cs.CL2024
Finetuning Generative Large Language Models with Discrimination Instructions for Knowledge Graph Completion
Yang Liu, Xiaobin Tian, Zequn Sun +1
Traditional knowledge graph (KG) completion models learn embeddings to predict missing facts. Recent works attempt to complete KGs in a text-generation manner with large language m…
cs.CL2024
Knowledge Graph Error Detection with Contrastive Confidence Adaption
Xiangyu Liu, Yang Liu, Wei Hu
Knowledge graphs (KGs) often contain various errors. Previous works on detecting errors in KGs mainly rely on triplet embedding from graph structure. We conduct an empirical study…