3 papers
cs.CY2026
VEAT Quantifies Implicit Associations in Text-to-Video Generator Sora and Reveals Challenges in Bias Mitigation
Yongxu Sun, Michael Saxon, Ian Yang +2
Text-to-Video (T2V) generators such as Sora raise concerns about whether generated content reflects societal bias. We extend embedding-association tests from words and images to vi…
cs.CV2025
CAIRe: Cultural Attribution of Images by Retrieval-Augmented Evaluation
Arnav Yayavaram, Siddharth Yayavaram, Simran Khanuja +2
As text-to-image models become increasingly prevalent, ensuring their equitable performance across diverse cultural contexts is critical. Efforts to mitigate cross-cultural biases…
cs.CL2025
Culture is Everywhere: A Call for Intentionally Cultural Evaluation
Juhyun Oh, Inha Cha, Michael Saxon +3
The prevailing ``trivia-centered paradigm'' for evaluating the cultural alignment of large language models (LLMs) is increasingly inadequate as these models become more advanced an…