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%0 Conference Proceedings
%T ModSCAN: Measuring Stereotypical Bias in Large Vision-Language Models from Vision and Language Modalities
%A Jiang, Yukun
%A Li, Zheng
%A Shen, Xinyue
%A Liu, Yugeng
%A Backes, Michael
%A Zhang, Yang
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F jiang-etal-2024-modscan
%R 10.18653/v1/2024.emnlp-main.713
%U https://aclanthology.org/2024.emnlp-main.713/
%U https://doi.org/10.18653/v1/2024.emnlp-main.713
%P 12814-12845

Markdown (Informal)

[ModSCAN: Measuring Stereotypical Bias in Large Vision-Language Models from Vision and Language Modalities](https://aclanthology.org/2024.emnlp-main.713/) (Jiang et al., EMNLP 2024)

• ModSCAN: Measuring Stereotypical Bias in Large Vision-Language Models from Vision and Language Modalities (Jiang et al., EMNLP 2024)

ACL

• Yukun Jiang, Zheng Li, Xinyue Shen, Yugeng Liu, Michael Backes, and Yang Zhang. 2024. ModSCAN: Measuring Stereotypical Bias in Large Vision-Language Models from Vision and Language Modalities. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 12814–12845, Miami, Florida, USA. Association for Computational Linguistics.