Papers by Zengwei Zheng

2 papers
Multimodal Sarcasm Target Identification in Tweets (2022.acl-long)

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Challenge: Existing methods to detect sarcasm target with text lacking context are not sufficient and complete.
Approach: They propose a multi-modal sarcasm target identification task that performs both textual and visual detection.
Outcome: The proposed model can perform textual target labeling and visual target detection.
RIVA: A Pre-trained Tweet Multimodal Model Based on Text-image Relation for Multimodal NER (2020.coling-main)

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Challenge: Named entity recognition (MNER) for tweets is a key task of many applications.
Approach: They propose a pre-trained multimodal named entity recognition model based on Relationship Inference and Visual Attention (RIVA) for tweets.
Outcome: The proposed model improves on the multimodal named entity recognition (MNER) task on tweets with the aid of visual clues.

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