Prompt-agnostic adversarial perturbation for customized diffusion models
Diffusion models have revolutionized customized text-to-image generation, allowing for
efficient synthesis of photos from personal data with textual descriptions. However, these …
efficient synthesis of photos from personal data with textual descriptions. However, these …
Adapter-Enhanced Semantic Prompting for Continual Learning
Continual learning (CL) enables models to adapt to evolving data streams. A major
challenge of CL is catastrophic forgetting, where new knowledge will overwrite previously …
challenge of CL is catastrophic forgetting, where new knowledge will overwrite previously …
ICL-TSVD: Bridging Theory and Practice in Continual Learning with Pre-trained Models
The goal of continual learning (CL) is to train a model that can solve multiple tasks
presented sequentially. Recent CL approaches have achieved strong performance by …
presented sequentially. Recent CL approaches have achieved strong performance by …
HyperAdapter: Generating Adapters for Pre-Trained Model-Based Continual Learning
Q Zhang, R An, B Zou, Z Zhang, S Zhang - openreview.net
Humans excel at leveraging past experiences to learn new skills, while artificial neural
networks suffer from the phenomenon of catastrophic forgetting during sequential learning …
networks suffer from the phenomenon of catastrophic forgetting during sequential learning …