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Most of SPA's baselines are Interpolation methods. And in its abstract:
Completing missing facts is a fundamental task for temporal knowledge graphs (TKGs).
So as to《Hierarchical Self-Attention Embedding for Temporal Knowledge Graph Completion》:
Experiments demonstrate that our model achieves better performance on TKGC interpolation tasks.
I doubt whether CENET is a Graph Neural Network-based TKGC Method.《Temporal Knowledge Graph Reasoning with Historical Contrastive Learning》.
The text was updated successfully, but these errors were encountered:
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Most of SPA's baselines are Interpolation methods.
And in its abstract:
So as to《Hierarchical Self-Attention Embedding for Temporal Knowledge Graph Completion》:
I doubt whether CENET is a Graph Neural Network-based TKGC Method.《Temporal Knowledge Graph Reasoning with Historical Contrastive Learning》.
The text was updated successfully, but these errors were encountered: