Papers by Dixiang Zhang

1 papers
Flat Multi-modal Interaction Transformer for Named Entity Recognition (2022.coling-1)

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Challenge: Named entity recognition (MNER) aims at identifying entity spans and recognizing their categories in social media posts with the aid of images.
Approach: They propose to use sentences and general domain words to obtain visual cues to transform the fine-grained semantic representation of vision and text into a unified lattice structure and leverage entity boundary detection as an auxiliary task to alleviate visual bias.
Outcome: The proposed method achieves state-of-the-art on two benchmark datasets.

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