Papers by Bosen Zhang

1 papers
RCL: Relation Contrastive Learning for Zero-Shot Relation Extraction (2022.findings-naacl)

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Challenge: Existing approaches to extract relations require large-scale labeled data.
Approach: They propose a Relation Contrastive Learning framework to mitigate similar relations and similar entities problems by optimizing a contrastive instance loss with a relation classification loss on seen relations.
Outcome: The proposed framework can learn subtle difference between instances and achieve better separation between different relation categories in the representation space simultaneously.

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