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Knowledge Diversion: A Novel Paradigm for Pre-training Decomposable Image Generation Models
Large-scale pre-trained models have become foundational to modern machine learning, yet conventional pre-training objectives primarily optimize source-domain performance without explicitly considering downstream requirements. Consequently, transferable and task-specific knowledge remains entangled w
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