Preprint
Aug 2026
DIFFCZSL: Compositional Zero-Shot Learning Regularized by Diffusion Representations
DIFFCZSL is proposed, a diffusion-augmented framework that injects generative priors from pre-trained diffusion models into CLIP-based CZSL pipelines and highlights the complementary strengths of generative diffusion representations and discriminative vision-language models for compositional generalization.
Hangyu Tian, Zhenqi He, Yanghao Wang et al.
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