Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...

Identifying optimal catalyst materials for specific reactions is crucial to advance energy storage technologies and sustainable chemical processes. To screen catalysts, scientists must understand ...

Abstract: Advancing Multimodal AI for Integrated Understanding and Generation explores the transformative potential of multimodal artificial intelligence (AI), which integrates diverse data types such ...

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...

Multimodal machine translation (MMT) represents an evolution from traditional text-only translation systems by integrating additional sources of information – typically images and videos – to support ...

New research presented during the 2024 San Antonio Breast Cancer Symposium (SABCS) reveals a new machine learning model that could change the way metastatic breast cancer is treated in the future. By ...

The development of bioinspired electronic skin plays a pivotal role in enhancing robotic environmental perception and ...

Pancreatic cancer mortality trends (2018-2023): Exposing racial inequities in Michigan's cancer burden. AUC for the PurIST baseline, the top 2 unimodal models, and the best fusion model for each ...

Artificial intelligence has transcended science fiction and firmly rooted itself in our reality. We’ve seen incredible progress, moving from deep learning and natural language processing (NLP) to ...

Trends in immune-related adverse event reporting among multidisciplinary cancer programs. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a full ...

Images are now parsed like language. OCR, visual context and pixel-level quality shape how AI systems interpret and surface content.