Tesnim Gülsen

Examining Racial and Gender Bias in CLIP via Explainability-Based Visual Attention Analysis

Vision-language models (VLMs) such as CLIP are increasingly integrated into automated decision-making systems where unexamined social biases can directly harm racial and gender minorities through discriminatory outcomes and unjust content censorship. Despite strong multimodal performance, CLIP's susceptibility to demog...