Latest AI and machine learning research in cultural competence for healthcare professionals.
We introduce Deep Spectral Prior (DSP), a new formulation of Deep Image Prior (DIP) that redefines...
This paper examines how large language models (LLMs) are transforming core quantitative methods in...
We investigate the existence and persistence of a specific type of gender bias in some of the popu...
Recent advances in Multimodal Large Language Models (MLLMs) have shown promising results in integr...
Person re-identification (ReID) models are known to suffer from camera bias, where learned represe...
As the marginal cost of scaling computation (data and parameters) during model pre-training contin...
Despite the impressive performance of generative Diffusion Models (DMs), their internal working is...
The biases exhibited by text-to-image (TTI) models are often treated as independent, though in rea...
Segment Anything Models (SAM) have achieved remarkable success in object segmentation tasks across...
Medical Visual Question Answering (MedVQA) is crucial for enhancing the efficiency of clinical dia...
BACKGROUND: The English National Health Service (NHS) strives for a fair, diverse, and inclusive wor...
Bias in Large Language Models (LLMs) significantly undermines their reliability and fairness. We f...
Although existing CLIP-based methods for detecting AI-generated images have achieved promising res...
With the advent of artificial intelligence (AI), novel opportunities arise to revolutionize healthca...
Personalizing 3D scenes from a single reference image enables intuitive user-guided editing, which...
Algorithmic tools are increasingly used in hiring to improve fairness and diversity, often by enfo...
Popularity bias occurs when popular items are recommended far more frequently than they should be,...
Multilingual vision-language models promise universal image-text retrieval, yet their social biase...
Deep learning models often achieve high performance by inadvertently learning spurious correlation...
Few-shot cross-modal retrieval focuses on learning cross-modal representations with limited traini...
How discriminative position information is for image classification depends on the data. On the on...