Recent studies have shown that Text-to-Image (T2I) model generations can reflect social stereotypes present in the real world. However, existing approaches for evaluating stereotypes have a noticeable lack of coverage of global identity groups and their associated stereotypes. To address this gap, we introduce the ViSAGe (Visual Stereotypes Around the Globe) dataset to enable the evaluation of known nationality-based stereotypes in T2I models, across 135 nationalities. We enrich an existing textual stereotype resource by distinguishing between stereotypical associations that are more likely to have visual depictions, such as `sombrero', from those that are less visually concrete, such as 'attractive'. We demonstrate ViSAGe's utility through a multi-faceted evaluation of T2I generations. First, we show that stereotypical attributes in ViSAGe are thrice as likely to be present in generated images of corresponding identities as compared to other attributes, and that the offensiveness of these depictions is especially higher for identities from Africa, South America, and South East Asia. Second, we assess the stereotypical pull of visual depictions of identity groups, which reveals how the 'default' representations of all identity groups in ViSAGe have a pull towards stereotypical depictions, and that this pull is even more prominent for identity groups from the Global South. CONTENT WARNING: Some examples contain offensive stereotypes.

翻译：近期研究表明，文本到图像（T2I）模型生成的内容能够反映现实世界中存在的社会刻板印象。然而，现有的刻板印象评估方法明显缺乏对全球身份群体及其相关刻板印象的覆盖。为弥补这一空白，我们引入了ViSAGe（全球视觉刻板印象）数据集，以评估T2I模型中基于135个国籍的已知刻板印象。我们通过区分更可能具有视觉描绘的刻板印象关联（如“宽边帽”）与视觉上较不具体的关联（如“有吸引力的”），对现有文本刻板印象资源进行了丰富。我们通过多维度评估T2I生成结果来证明ViSAGe的实用性。首先，我们发现ViSAGe中的刻板印象属性在对应身份生成图像中出现的可能性是其他属性的三倍，且这些描绘的冒犯性对来自非洲、南美洲和东南亚的身份群体尤为突出。其次，我们评估了身份群体视觉描绘的刻板印象吸引力，揭示了ViSAGe中所有身份群体的“默认”表征均存在向刻板描绘靠拢的趋势，且这种趋势对全球南方身份群体更为显著。内容警示：部分示例包含冒犯性刻板印象。