Abstract: Graph Attention Networks (GAT) is a type of neural network architecture designed to effectively model and process data represented as graphs. GATs leverage the concept of attention ...
This system takes an unstructured text document, and uses an LLM of your choice to extract knowledge in the form of Subject-Predicate-Object (SPO) triplets, and visualizes the relationships as an ...
Abstract: Contrastive learning (CL) has recently sparked a productive line of research in the field of recommendation, due to its ability to extract self-supervised signals from raw data that align ...
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