Papers by Xiaojuan Tang

1 papers
RulE: Knowledge Graph Reasoning with Rule Embedding (2024.findings-acl)

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Challenge: Knowledge graph reasoning is an important problem for knowledge graphs.
Approach: They propose a framework that leverages logical rules to enhance KG reasoning by learning rule embeddings from existing triplets and first-order rules.
Outcome: The proposed framework outperforms existing embedding-based and rule-based methods on multiple benchmarks.

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