3 papers
cs.CL2025
Breaking Language Barriers or Reinforcing Bias? A Study of Gender and Racial Disparities in Multilingual Contrastive Vision Language Models
Zahraa Al Sahili, Ioannis Patras, Matthew Purver
Multilingual vision-language models (VLMs) promise universal image-text retrieval, yet their social biases remain underexplored. We perform the first systematic audit of four publi…
cs.AI2025
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
cs.LG2025
Data Matters Most: Auditing Social Bias in Contrastive Vision Language Models
Zahraa Al Sahili, Ioannis Patras, Matthew Purver
Vision-language models (VLMs) deliver strong zero-shot recognition but frequently inherit social biases from their training data. We systematically disentangle three design factors…