NP-LoRA fuses subject and style LoRAs via null-space projection of the content update onto the orthogonal complement of the style subspace, with a soft variant controlled by one parameter.
Diffusion models beat gans on image synthesis
2 Pith papers cite this work. Polarity classification is still indexing.
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EMSFD uses Dirichlet-based evidence modeling to capture prediction uncertainty in synthetic face detection and applies uncertainty-driven active learning to achieve 15% higher accuracy than prior methods.
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NP-LoRA: Null Space Projection for Subject-Style LoRA Fusion
NP-LoRA fuses subject and style LoRAs via null-space projection of the content update onto the orthogonal complement of the style subspace, with a soft variant controlled by one parameter.
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Evidence-based Decision Modeling for Synthetic Face Detection with Uncertainty-driven Active Learning
EMSFD uses Dirichlet-based evidence modeling to capture prediction uncertainty in synthetic face detection and applies uncertainty-driven active learning to achieve 15% higher accuracy than prior methods.