March 27, 2024, 4:48 a.m. | Veronika Grigoreva, Anastasiia Ivanova, Ilseyar Alimova, Ekaterina Artemova

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.17553v1 Announce Type: new
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 …

abstract arxiv behavior bias biases cs.cl data dataset datasets detection fair functional language language models large language large language models learn llm llms pre-training raw social test training training data type work

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Principal Data Engineering Manager

@ Microsoft | Redmond, Washington, United States

Machine Learning Engineer

@ Apple | San Diego, California, United States