Year: 2026
Type: conference-paper
Abstract: While gender and racial biases in language models have been widely studied, anti-LGBTQ biases remain underexplored, particularly beyond English.Existing benchmarks often do not capture cultural and linguistic variation and rely on gender representations.This paper introduces a multilingual German-English benchmark dataset for the evaluation of anti-LGBTQ biases in language models.It combines community-sourced stereotypes from German-speaking queer individuals with a German translation of WinoQueer.The data is used to evaluate eight language models across sizes and architectures and explore mitigation through fine-tuning on community and progressive media content.Results show that language models reproduce anti-queer stereotypes, with variation across identities and models.Differences between the translated and communitybased data highlight the importance of cultural adaptation for multilingual bias evaluation.Fine-tuning reduces bias on average, but not consistently across models and identities.Warning: This text contains examples of antiqueer hateful language and stereotypes.
Authors: Melina Morch, Daniel Braun
Institution: Philipps University of Marburg
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: hybrid
OpenAlex ID: W7204935255