Papers by Héctor Pérez-Urbina
A Comprehensive Framework to Operationalize Social Stereotypes for Responsible AI Evaluations (2025.emnlp-main)
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| Challenge: | Recent years have seen unprecedented gains in generative AI models' capabilities across modalitieslanguage, image, audio, and video domains across the globe. |
| Approach: | They propose a framework to operationalize stereotypes in generative AI evaluations using social psychological research and NLP data. |
| Outcome: | The proposed framework identifies key components of stereotypes that are crucial in AI evaluation, including the target group, associated attribute, relationship characteristics, perceiving group, and context. |