Papers by Xuanyu Su

1 papers
A Context-Aware Contrastive Learning Framework for Hateful Meme Detection and Segmentation (2025.findings-naacl)

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Challenge: Empirical experiments show HateSieve surpasses existing LMMs in performance with fewer trainable parameters .
Approach: They propose a framework to enhance detection and segmentation of hateful elements in memes by creating a triplet dataset and an Image-Text Alignment module.
Outcome: HateSieve features a new framework that creates semantically correlated memes and generates contextual embeddings for accurate meme segmentation.

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