ETT-CKGE replaces manual importance scoring in continual knowledge graph embedding with learned token masks, achieving competitive accuracy with much lower training time and memory.
In: Proceedings of the AAAI Conference on Artificial Intelligence
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ETT-CKGE: Efficient Task-driven Tokens for Continual Knowledge Graph Embedding
ETT-CKGE replaces manual importance scoring in continual knowledge graph embedding with learned token masks, achieving competitive accuracy with much lower training time and memory.