Latest AI and machine learning research in cultural competence for healthcare professionals.
The use of CLIP embeddings to assess the alignment of samples produced by text-to-image generative...
Large language models (LLMs) have brought exciting new advances to mobile UI agents, a long-standi...
Multimodal machine learning models, such as those that combine text and image modalities, are incr...
Disease progression models are widely used to inform the diagnosis and treatment of many progressi...
Generative AI models like GPT-4o and DALL-E 3 are reshaping digital content creation, offering ind...
Recently, 3D generative domain adaptation has emerged to adapt the pre-trained generator to other ...
Robust Principal Component Analysis (RPCA) is a fundamental technique for decomposing data into lo...
We propose CAD-Assistant, a general-purpose CAD agent for AI-assisted design. Our approach is base...
CNNs have become one of the most commonly used computational tool in the past two decades. One of ...
Large language models (LLMs) have shown promising capabilities in healthcare analysis but face sev...
Graph Neural Networks (GNNs) perform effectively when training and testing graphs are drawn from t...
This paper proposes a novel interdisciplinary framework for the critical evaluation of text-to-ima...
Generalized Category Discovery is a significant and complex task that aims to identify both known ...
Software engineering (SE) faces significant diversity challenges in both academia and industry, wi...
Domain Generalized Semantic Segmentation (DGSS) seeks to utilize source domain data exclusively to...
This study investigates the trade-offs between fairness, privacy, and utility in image classificat...
Data-free knowledge distillation transfers knowledge by recovering training data from a pre-traine...
Most of the ML datasets we use today are biased. When we train models on these biased datasets, th...
Artificial Intelligence (AI) is a broad field that is upturning mental health care in many ways, f...
Bias significantly undermines both the accuracy and trustworthiness of machine learning models. To...
Machine learning (ML) algorithms have become integral to decision making in various domains, inclu...