3 papers
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.CL2023
Generating Explanations to Understand and Repair Embedding-based Entity Alignment
Xiaobin Tian, Zequn Sun, Wei Hu
Entity alignment (EA) seeks identical entities in different knowledge graphs, which is a long-standing task in the database research. Recent work leverages deep learning to embed e…
cs.CL2022
EventEA: Benchmarking Entity Alignment for Event-centric Knowledge Graphs
Xiaobin Tian, Zequn Sun, Guangyao Li +1
Entity alignment is to find identical entities in different knowledge graphs (KGs) that refer to the same real-world object. Embedding-based entity alignment techniques have been d…