Shu Zhao

The Value of Being Wrong: Self-Mined Visual In-Context Learning from Errors

Visual in-context learning (ICL) enables vision-language models (VLMs) to adapt at test time via demonstration examples, but its effectiveness depends critically on the examples selected. Recent counterfactual selection methods improve ICL by constructing demonstrations that expose how individual attribute changes affe...