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SeqLoRA: Bilevel Orthogonal Adaptation for Continual Multi-Concept Generation
Parameter-efficient fine-tuning enables fast personalization of text-to-image diffusion models to user-provided concepts (objects, people, or styles), but composing multiple such concepts remains challenging due to representation interference. Existing modular methods, usually built on low-rank adap
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