Large language models (LLMs) have significantly advanced the field of natural language
processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of …

With the prevalence of pre-trained language models (PLMs) and the pre-training–fine-tuning
paradigm, it has been continuously shown that larger models tend to yield better …

As generative large language models (LLMs) grow more performant and prevalent, we must
develop comprehensive enough tools to measure and improve their fairness. Different …

Large Language Models (LLMs) such as ChatGPT, have gained significant attention due to
their impressive natural language processing capabilities. It is crucial to prioritize human …

In recent years, the rapid advancement of machine learning (ML) models, particularly
transformer-based pre-trained models, has revolutionized Natural Language Processing …

Perception of toxicity evolves over time and often differs between geographies and cultural
backgrounds. Similarly, black-box commercially available APIs for detecting toxicity, such as …

Considerable effort has been dedicated to mitigating toxicity, but existing methods often
require drastic modifications to model parameters or the use of computationally intensive …

Rapid advancements of large language models (LLMs) have enabled the processing,
understanding, and generation of human-like text, with increasing integration into systems …

Generative artificial intelligence has made significant strides, producing text
indistinguishable from human prose and remarkably photorealistic images. Automatically …

Warning: this paper includes model outputs showing offensive content. Recent large-scale
Visual-Language Generative Models (VLGMs) have achieved unprecedented improvement …