Papers by Duo Dong

1 papers
Global Structure Knowledge-Guided Relation Extraction Method for Visually-Rich Document (2023.findings-emnlp)

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Challenge: Existing methods focus on manipulating entity features to find pairwise relations, yet neglect the more fundamental structural information that links disparate entity pairs together.
Approach: They propose a Visual Relation Extraction framework that generates relation predictions on entity pairs extracted from scanned images and incorporates global structural knowledge into the representations of the entities.
Outcome: The proposed framework outperforms existing methods in fine-tuning setting and yields stronger data-efficient performance in the low-resource setting.

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