
Two-dimensional feature engineering can take advantage of a two-dimensional sentence representation and make full use of prior knowledge to improve relation extraction performance.


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a-two-dimensional-feature-engineering-method-for-relation-extraction


A Two-Dimensional Feature Engineering Method for Relation Extraction


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Current relation extraction models excessively rely on entities, making them vulnerable to adversarial attacks and limiting their generalization. An adversarial training method is proposed to address this issue by introducing both sequence- and token-level perturbations and a probabilistic strategy to encourage the model to leverage relational patterns in the context.


improving-relation-extraction-by-mitigating-over-dependency-on-entities-through-adversarial-training


Improving Relation Extraction by Mitigating Over-Dependency on Entities through Adversarial Training
