{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/rubia-a-russian-language-bias-detection","title":"RuBia: A Russian Language Bias Detection Dataset","arxiv_id":"2403.17553","date":"2024-03-26","proceeding":null,"authors":["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.","url_abs":"https://arxiv.org/abs/2403.17553v1","url_pdf":"https://arxiv.org/pdf/2403.17553v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"rubia-a-russian-language-bias-detection","repo_url":"https://github.com/vergrig/RuBia-Dataset","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"CC-BY-4.0"}}],"tasks":[{"task_slug":"bias-detection","task_name":"Bias Detection"},{"task_slug":"diagnostic","task_name":"Diagnostic"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2403.17553","atlas_url":"https://app.syntology.ai/?focus=2403.17553","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}