Papers by Jianghangfan Zhang

1 papers
Prior Relational Schema Assists Effective Contrastive Learning for Inductive Knowledge Graph Completion (2024.lrec-main)

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Challenge: Existing knowledge graphs lack robustness and incompleteness to provide link prediction.
Approach: They propose to capture prior schema-level interactions related to relations by leveraging entity type information and introduce schema-guided negatives to bolster the efficiency of normal contrastive representation learning.
Outcome: The proposed method achieves state-of-the-art performance on multiple established metrics across multiple datasets for link prediction.

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