Papers with diagnostic evaluation of state-of-the-art or near-state-of-the-art

1 papers
RuBia: A Russian Language Bias Detection Dataset (2024.lrec-main)

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Challenge: Large language models (LLMs) tend to learn the social and cultural biases present in the raw pre-training data.
Approach: They present a bias detection dataset specifically designed for the Russian language, dubbed RuBia, which is divided into 4 domains: gender, nationality, socio-economic status, and diverse.
Outcome: The proposed dataset is designed to detect bias in the Russian language and is based on 2,000 unique sentence pairs spread over 19 subdomains.

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