1 research outputs found
Adversarial Learning for Supervised and Semi-supervised Relation Extraction in Biomedical Literature
Adversarial training is a technique of improving model performance by
involving adversarial examples in the training process. In this paper, we
investigate adversarial training with multiple adversarial examples to benefit
the relation extraction task. We also apply adversarial training technique in
semi-supervised scenarios to utilize unlabeled data. The evaluation results on
protein-protein interaction and protein subcellular localization task
illustrate adversarial training provides improvement on the supervised model,
and is also effective on involving unlabeled data in the semi-supervised
training case. In addition, our method achieves state-of-the-art performance on
two benchmarking datasets