@inproceedings{aghazadeh-kovashka-2025-face,
    title = "The Face of Persuasion: Analyzing Bias and Generating Culture-Aware Ads",
    author = "Aghazadeh, Aysan  and
      Kovashka, Adriana",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.344/",
    doi = "10.18653/v1/2025.findings-emnlp.344",
    pages = "6472--6500",
    ISBN = "979-8-89176-335-7",
    abstract = "Text-to-image models are appealing for customizing visual advertisements and targeting specific populations. We investigate this potential by examining the demographic bias within ads for different ad topics, and the disparate level of persuasiveness (judged by models) of ads that are identical except for gender/race of the people portrayed. We also experiment with a technique to target ads for specific countries."
}