Unlearning for CLIP Models: A Novel Training- and Data-Free Approach

This research explores a novel method for unlearning in CLIP models, crucial for addressing data privacy and model bias. The data-free approach could significantly enhance the flexibility and applicability of these models across various domains.

• •Presents a data-free unlearning approach for CLIP models.
• •Addresses crucial aspects of data privacy and model bias.
• •Potentially broadens the application of CLIP models across diverse areas.