DIFFCZSL: Compositional Zero-Shot Learning Regularized by Diffusion Representations

Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object compositions by leveraging knowledge of primitive concepts learned from seen compositions. Although recent works achieve impressive performance in CZSL by leveraging large vision-language models, they primarily rely on discriminative representations that may not explicitly preserve the structured relationships between primitive concepts and their compositions.

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• llms
• rag
• diffusion
• multimodal
• benchmarks
• safety