Despite CLIP being the foundation model in numerous vision-language applications, CLIP
suffers from a severe text spotting bias. Such bias causes CLIP models to 'Parrot'the visual …

With the growing popularity of text-to-image generative models, there has been increasing
focus on understanding their risks and biases. Recent work has found that state-of-the-art …

CLIP has demonstrated great versatility in adapting to various downstream tasks, such as
image editing and generation, visual question answering, and video understanding …

Unlike human-engineered systems such as aeroplanes, where each component's role and
dependencies are well understood, the inner workings of AI models remain largely opaque …

The rapid advancement of large language models (LLMs) and multimodal learning has
transformed digital content creation and manipulation. Traditional visual editing tools require …

Bias in Foundation Models (FMs)-trained on vast datasets spanning societal and historical
knowledge-poses significant challenges for fairness and equity across fields such as …

Large-scale vision-language models, such as CLIP, are known to contain harmful societal
bias regarding protected attributes (eg, gender and age). In this paper, we aim to address …

The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes
the refereed proceedings of the 18th European Conference on Computer Vision, ECCV …

Since 2022, the growing attention to and public accessibility of generative artificial
intelligence (AI) have become essential for knowledge acquisition on digital platforms …