Papers with triple prediction task

1 papers
Debiasing knowledge graph embeddings (2020.emnlp-main)

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Challenge: Existing methods to train knowledge graph embeddings to be neutral to sensitive attributes such as gender have been shown to increase training time by a factor of eight or more.
Approach: They propose a method where all embeddings are trained to be neutral to sensitive attributes such as gender by default using an adversarial loss.
Outcome: The proposed method reduces training time by eightfold and improves accuracy.

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