StereoTales: A Multilingual Framework for Open-Ended Stereotype Discovery in LLMs
Multilingual studies of social bias in open-ended LLM generation remain limited: most existing benchmarks are English-centric, template-based, or restricted to recognizing pre-specified stereotypes. We introduce StereoTales, a multilingual dataset and evaluation pipeline for systematically studying the emergence of social bias in open-ended LLM generation. The dataset covers 10 languages and 79 socio-demographic attributes, and comprises over 650k stories generated by 23 recent LLMs, each annotated with the socio-demographic profile of the protagonist across 19 dimensions. From these, we apply statistical tests to identify more than 1{,}500 over-represented associations, which we then rat...
| Authors | Pierre Le Jeune, Étienne Duchesne, Weixuan Xiao et al. |
|---|---|
| Primary category | cs.CY |
| Published | 11 May 2026 |
| Last updated at source | 12 May 2026 |
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