Peer review UpCwGBfq

This paper focuses on the challenge of detecting stereotypes in LLM-generated language by studying the expression of generalizations. It proposes a multilingual dataset GeniL that is annotated for generalizations. The experimental results show that the mere co-occurrence of an identity term and attribute being a generalization is generally unlikely and varies by language, identity group, and attribute. The authors also train classifiers on the proposed dataset to improve the performance of generalization detection.