TransFIR enables reasoning on temporal knowledge graphs for emerging entities by clustering them into semantic groups and borrowing interaction histories from similar known entities, yielding 28.6% average MRR gains.
All LLM-generated content was thoroughly reviewed and validated by the authors to ensure the accuracy of the pre- sented information
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Inductive Reasoning for Temporal Knowledge Graphs with Emerging Entities
TransFIR enables reasoning on temporal knowledge graphs for emerging entities by clustering them into semantic groups and borrowing interaction histories from similar known entities, yielding 28.6% average MRR gains.