Gender Bias in Large Language Models across Multiple Languages

arXiv:2403.00277v1 Announce Type: new
Abstract: With the growing deployment of large language models (LLMs) across various applications, assessing the influence of gender biases embedded in LLMs becomes crucial. The topic of gender bias within the realm of natural language processing (NLP) has gained considerable focus, particularly in the context of English. Nonetheless, the investigation of gender bias in languages other than English is still relatively under-explored and insufficiently analyzed. In this work, We examine gender bias in LLMs-generated outputs for …

abstract applications arxiv bias biases context cs.cl deployment embedded english focus gender gender bias influence language language models language processing languages large language large language models llms multiple natural natural language natural language processing nlp processing type