Papers by Khai Phan Tran

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Challenge:	Existing methods for Document-level Relation Extraction assume a uniform label distribution, resulting in suboptimal performance on real-world, imbalanced datasets.
Approach:	They propose a method that leverages the Variational Autoencoder architecture to capture all relation-wise distributions formed by entity pair representations and augment data for underrepresented relations.
Outcome:	The proposed method outperforms state-of-the-art models on two benchmark datasets and is available on github.