Papers by Jiangong Yang

1 papers
Consistent Representation Learning for Continual Relation Extraction (2022.findings-acl)

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Challenge: Existing methods to train relation extraction models overfit memory samples and perform poorly on imbalanced datasets.
Approach: They propose a method which uses contrastive learning and knowledge distillation to train a model on data with new relations while avoiding forgetting old ones.
Outcome: The proposed method significantly outperforms state-of-the-art baselines and yields strong robustness on the imbalanced datasets.

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