Xinghua Qu

We propose the first robust weak-to-strong generalization framework to elicit robust knowledge from a strong student VLM in an unsupervised scheme.

VLM unlearning by a closed-form ensemble of infinite number of functions with parameters uniformly sampled from a task arithmetic simplex.