Safeguarding Large Language Models: A Survey

Y Dong, R Mu, Y Zhang, S Sun, T Zhang, C Wu… - arXiv preprint arXiv …, 2024 - arxiv.org
In the burgeoning field of Large Language Models (LLMs), developing a robust safety
mechanism, colloquially known as" safeguards" or" guardrails", has become imperative to …

Enhancing Gender-Inclusive Machine Translation with Neomorphemes and Large Language Models

A Piergentili, B Savoldi, M Negri… - arXiv preprint arXiv …, 2024 - arxiv.org
Machine translation (MT) models are known to suffer from gender bias, especially when
translating into languages with extensive gendered morphology. Accordingly, they still fall …

Robust Pronoun Use Fidelity with English LLMs: Are they Reasoning, Repeating, or Just Biased?

V Gautam, E Bingert, D Zhu, A Lauscher… - arXiv preprint arXiv …, 2024 - arxiv.org
Robust, faithful and harm-free pronoun use for individuals is an important goal for language
models as their use increases, but prior work tends to study only one or two of these …

Gender and representation: investigations of bias in natural language processing

H Devinney - 2024 - diva-portal.org
Abstract Natural Language Processing (NLP) technologies are a part of our every day
realities. They come in forms we can easily see as 'language technologies'(autocorrect …