The trustworthiness of machine learning has emerged as a critical topic in the field,
encompassing various applications and research areas such as robustness, security …

As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly
prevalent and seeing growing adoption as commercial services, characterizing the social …

Machine learning models are commonly used to detect toxicity in online conversations.
These models are trained on datasets annotated by human raters. We explore how raters' …

Based on the foundation of Large Language Models (LLMs), Multilingual LLMs (MLLMs)
have been developed to address the challenges faced in multilingual natural language …

With language models becoming increasingly ubiquitous, it has become essential to
address their inequitable treatment of diverse demographic groups and factors. Most …

A variety of fairness constraints have been proposed in the literature to mitigate group-level
statistical bias. Their impacts have been largely evaluated for different groups of populations …

We explore the extent to which zero-shot vision-language models exhibit gender bias for
different vision tasks. Vision models traditionally required task-specific labels for …

Abstract Text-to-Image (TTI) generative models have shown great progress in the past few
years in terms of their ability to generate complex and high-quality imagery. At the same …

We address the challenge of generating fair and unbiased image retrieval results given
neutral textual queries (with no explicit gender or race connotations), while maintaining the …

The rapid development of Large Language Models (LLMs) demonstrates remarkable
multilingual capabilities in natural language processing, attracting global attention in both …