The article presents a study on the use of Graph Neural Networks (GNNs) for link prediction in heterophilic graphs. The authors introduce GRAFF-LP, an extension to the physics-inspired GRAFF model,…
Continue readingThe article discusses how large language models (LLMs), despite their exceptional applicative potential, have not been effectively used in mining relationships from graph data. The authors propose a framework that…
Continue readingThe article presents the Patent Office Action Response Intelligence System (PARIS) and its advanced version, the Large Language Model Enhanced PARIS (LE-PARIS). These systems aim to increase the efficiency of…
Continue readingThe study introduces ‘WellFactor’, a method that creates comprehensive patient profiles using not only traditional medical records but also diverse data sets from healthcare web portals. The approach uses constrained…
Continue readingHuman-Machine Interfaces (HMIs) are essential for communication between humans and machines. The study delves into the transformation of static HMIs into Adaptive User Interfaces (AUIs) that adapt according to individual…
Continue readingThis paper presents a novel perspective on Click-Through Rate (CTR) prediction tasks, commonly used in recommendation systems. Rather than considering CTR prediction as a static task, the authors advocate for…
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