CrossFlowDG bridges the modality gap in domain generalization by learning a continuous transformation that moves image embeddings to matching text embeddings using noise-free cross-modal flow matching.
Deep unsupervised learning using nonequilibrium thermodynamics
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GrOCE uses dynamic semantic graphs for online, training-free erasure of target concepts from diffusion model prompts via cluster identification and selective severing.
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CrossFlowDG: Bridging the Modality Gap with Cross-modal Flow Matching for Domain Generalization
CrossFlowDG bridges the modality gap in domain generalization by learning a continuous transformation that moves image embeddings to matching text embeddings using noise-free cross-modal flow matching.
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GrOCE:Graph-Guided Online Concept Erasure for Text-to-Image Diffusion Models
GrOCE uses dynamic semantic graphs for online, training-free erasure of target concepts from diffusion model prompts via cluster identification and selective severing.