ModSCAN: Measuring Stereotypical Bias in Large Vision-Language Models from Vision and Language Modalities
Yukun Jiang, Zheng Li, Xinyue Shen, Yugeng Liu, Michael Backes, Yang Zhang
- Anthology ID:
- 2024.emnlp-main.713
- Volume:
- Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
- Month:
- November
- Year:
- 2024
- Address:
- Miami, Florida, USA
- Editors:
- Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 12814–12845
- Language:
- URL:
- https://preview.aclanthology.org/ingest_wac_2008/2024.emnlp-main.713/
- DOI:
- 10.18653/v1/2024.emnlp-main.713
- Cite (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.
- Cite (Informal):
- ModSCAN: Measuring Stereotypical Bias in Large Vision-Language Models from Vision and Language Modalities (Jiang et al., EMNLP 2024)
- PDF:
- https://preview.aclanthology.org/ingest_wac_2008/2024.emnlp-main.713.pdf