Tingrui Qiao

CABIN: Debiasing Vision-Language Models Using Backdoor Adjustments

Vision-language models (VLMs) have demonstrated strong zero-shot inference capabilities but may exhibit stereotypical biases toward certain demographic groups. Consequently, downstream tasks leveraging these models may yield unbalanced performance across different target social groups, potentially r