Abstract: Previous research on Knowledge Graph-to-Text Generation (KG-to-Text) primarily introduced auxiliary pretraining tasks to enhance pre-trained generative models, aiming to address their ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Abstract: Text classification is a critical task for understanding the knowledge behind text, especially in medical text. In this paper, we propose a medical graph diffusion model, named the MGD model ...

What if you could transform vast amounts of unstructured text into a living, breathing map of knowledge—one that not only organizes information but reveals hidden connections you never knew existed?

GENEVA, April 1(Reuters) - From its sleek headquarters on the shores of Lake Geneva, the World Trade Organization hopes to quietly ride out the after-shocks of Trump administration tariffs whose ...

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. If the Supreme Court sides with South ...

Multimodal Attributed Graphs (MMAGs) have received little attention despite their versatility in image generation. MMAGs represent relationships between entities with combinatorial complexity in a ...

mcplot provides a class that combines methods to easily produce publication-ready graphics on light or black background. It includes a large number of colormaps collected from different sources. There ...