Latest AI and machine learning research in medicare for healthcare professionals.
Imitation learning frameworks for robotic manipulation have drawn attention in the recent developm...
We address the long-horizon mapless navigation problem: enabling robots to traverse novel environm...
Diffusion MRI tractography technique enables non-invasive visualization of the white matter pathwa...
As research in the Scientometric deepens, the impact of data quality on research outcomes has garn...
Advancing AI in computational pathology requires large, high-quality, and diverse datasets, yet ex...
Generating knowledge-intensive and comprehensive long texts, such as encyclopedia articles, remain...
Online platforms like Pinterest hosting vast content collections traditionally rely on manual cura...
Precise Event Spotting (PES) aims to identify events and their class from long, untrimmed videos, ...
Uncertainty quantification is necessary for developers, physicians, and regulatory agencies to bui...
Multimodal large language models (MLLMs) have enabled open-world visual understanding by injecting...
Quantum federated learning (QFL) merges the privacy advantages of federated systems with the compu...
We introduce COU: Common Objects Underwater, an instance-segmented image dataset of commonly found...
Long-context Multimodal Large Language Models (MLLMs) that incorporate long text-image and text-vi...
Novel research aimed at text-to-image (T2I) generative AI safety often relies on publicly availabl...
Medicare fraud poses a substantial challenge to healthcare systems, resulting in significant finan...
Testing processes usually aim at high coverage, but loops severely limit coverage ambitions since ...
Existing Large Vision-Language Models (LVLMs) can process inputs with context lengths up to 128k v...
Purpose: Comprehensive legal medicine documentation includes both an internal but also an external...
Accurately locating key moments within long videos is crucial for solving long video understanding...
Single-cell proteomics (SCP) is transforming our understanding of biological complexity by shiftin...
The efficient processing of long context poses a serious challenge for large language models (LLMs...