More Than Sum of Its Parts: Deciphering Intent Shifts in Multimodal Hate Speech Detection
Combating hate speech on social media is critical for securing cyberspace, yet relies heavily on the efficacy of automated detection systems. As content formats evolve, hate speech is transitioning from solely plain text to complex multimodal expressions, making implicit attacks harder to spot. Current systems, however, often falter on these subtle cases, as they struggle with multimodal content where the emergent meaning transcends the aggregation of individual modalities. To bridge this gap, we move beyond binary classification to characterize semantic intent shifts where modalities interact to construct implicit hate from benign cues or neutralize toxicity through semantic inversion. G...
| Authors | Runze Sun, Yu Zheng, Zexuan Xiong et al. |
|---|---|
| Primary category | cs.CL |
| Published | 22 March 2026 |
| Last updated at source | 21 April 2026 |
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