Papers with KG-BERT

1 papers
Multi-Task Learning for Knowledge Graph Completion with Pre-trained Language Models (2020.coling-main)

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Challenge: Existing knowledge graph completion methods are lacking in ranking metrics such as Hits@k . despite the high performance, the proposed method is still behind state-of-the-art models.
Approach: They propose a multi-task learning method that integrates relational and relevance ranking tasks with target link prediction to improve ranking performance.
Outcome: The proposed method improves ranking performance but still behind state-of-the-art models in Hits@k and Mean Rank metrics.

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