Papers by Xicheng Lu

1 papers
KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion (2024.lrec-main)

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Challenge: Knowledge graph completion (KGC) is a critical task to predict missing facts among entities.
Approach: They propose a knowledge-constrained generative re-ranking method based on generative large language models for KGC that can predict missing facts among entities.
Outcome: The proposed method achieves state-of-the-art performance on four datasets and 9.0% and 11.1% compared to the previous methods.

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