Papers by François-Paul Servant

1 papers
Knowledge Base Embedding By Cooperative Knowledge Distillation (2020.coling-main)

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Challenge: Knowledge bases are increasingly exploited as gold standard data sources for various knowledge-driven NLP tasks.
Approach: They propose a method to perform knowledge base representation learning by mutually and jointly distilling knowledge within a dynamic teacher-student setting.
Outcome: The proposed approach outperforms two baselines, traditional and sequential, on two standard datasets showing that it is possible to distill knowledge between KBs.

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