AI RESEARCH
DARC-CLIP: Dynamic Adaptive Refinement with Cross-Attention for Meme Understanding
arXiv CS.CL
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ArXi:2604.23214v2 Announce Type: new Memes convey meaning through the interaction of visual and textual signals, often combining humor, irony, and offense in subtle ways. Detecting harmful or sensitive content in memes requires accurate modeling of these multimodal cues. Existing CLIP-based approaches rely on static fusion, which struggles to capture fine grained dependencies between modalities. We propose DARC-CLIP, a CLIP-based framework for adaptive multimodal fusion with a hierarchical refinement stack.