Papers by Xin Mei

1 papers
An Adaptive Logical Rule Embedding Model for Inductive Reasoning over Temporal Knowledge Graphs (2022.emnlp-main)

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Challenge: Existing methods for temporal knowledge graphs (TKGs) are incomplete and therefore lack interpretability.
Approach: They propose an interpretable temporal knowledge graph reasoning model that captures deep causal logic by learning rule embeddings.
Outcome: The proposed model outperforms state-of-the-art models on the ICEWS14, ICEW0515 and ICEw18 datasets.

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