Generic and Trend-aware Curriculum Learning for Relation Extraction
Nidhi Vakil, Hadi Amiri · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · 2022
We present a generic and trend-aware curriculum learning approach for graph neural networks.It extends existing approaches by incorporating sample-level loss trends to better discriminate easier from harder samples and schedule them for training.The model effectively integrates textual and structural information for relation extraction in text graphs.Experimental results show that the model provides robust estimations of sample difficulty and shows sizable improvement over the stateof-the-art approaches across several datasets.