CLASP: Continual Low-rank Adapters for Spatially Placed Concepts from One Hypernetwork

arXiv:2610.01331 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Code: https://github.com/genwro-ai/clasp

Terminology

• Hypernetwork — 62× in this paper · explained in 2 episodes
• Adaptation — 31× in this paper · explained in 1 episode
• Embeddings — 31× in this paper · explained in 2 episodes
• Personalization — 31× in this paper · explained in 2 episodes
• Diffusion Model — 24× in this paper · explained in 8 episodes
• Alignment — 20× in this paper · explained in 1 episode
• Benchmark — 18× in this paper · explained in 2 episodes
• Continual Learning — 18× in this paper · explained in 2 episodes
• Diffusion Models — 15× in this paper · explained in 6 episodes
• Fine-Tuning — 12× in this paper · explained in 5 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• Regularization — 6× in this paper · explained in 3 episodes
• Grounding — 5× in this paper · explained in 3 episodes
• In International Conference on Learning Representations — 5× in this paper
• Latent Diffusion Model — 5× in this paper · explained in 2 episodes
• International Conference on Computer Vision — 4× in this paper
• Catastrophic Forgetting — 3× in this paper · explained in 5 episodes
• Distillation — 3× in this paper · explained in 2 episodes
• Latent Diffusion Models — 3× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Concept-Incremental Flexible Customization — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Denoising Diffusion Probabilistic Models
• SeqLoRA: Bilevel Orthogonal Adaptation for Continual Multi-Concept Generation

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