RuBia: A Russian Language Bias Detection Dataset

Veronika Grigoreva, Anastasiia Ivanova, Ilseyar Alimova, Ekaterina Artemova


Abstract
Warning: this work contains upsetting or disturbing content. Large language models (LLMs) tend to learn the social and cultural biases present in the raw pre-training data. To test if an LLM’s behavior is fair, functional datasets are employed, and due to their purpose, these datasets are highly language and culture-specific. In this paper, we address a gap in the scope of multilingual bias evaluation by presenting a bias detection dataset specifically designed for the Russian language, dubbed as RuBia. The RuBia dataset is divided into 4 domains: gender, nationality, socio-economic status, and diverse, each of the domains is further divided into multiple fine-grained subdomains. Every example in the dataset consists of two sentences with the first reinforcing a potentially harmful stereotype or trope and the second contradicting it. These sentence pairs were first written by volunteers and then validated by native-speaking crowdsourcing workers. Overall, there are nearly 2,000 unique sentence pairs spread over 19 subdomains in RuBia. To illustrate the dataset’s purpose, we conduct a diagnostic evaluation of state-of-the-art or near-state-of-the-art LLMs and discuss the LLMs’ predisposition to social biases.
Anthology ID:
2024.lrec-main.1240
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
14227–14239
Language:
URL:
https://aclanthology.org/2024.lrec-main.1240
DOI:
Bibkey:
Cite (ACL):
Veronika Grigoreva, Anastasiia Ivanova, Ilseyar Alimova, and Ekaterina Artemova. 2024. RuBia: A Russian Language Bias Detection Dataset. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 14227–14239, Torino, Italia. ELRA and ICCL.
Cite (Informal):
RuBia: A Russian Language Bias Detection Dataset (Grigoreva et al., LREC-COLING 2024)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.1240.pdf