Relational graph convolutional network (R-GCN)

A Relational Graph Convolutional Network (R-GCN) is a type of neural network designed to operate on graph-structured data with multiple types of edges, enabling effective learning over relational data. It extends traditional graph convolutional networks by incorporating relation-specific transformations, making it particularly useful for knowledge graphs and multi-relational data.

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ByT5

ByT5 is a transformer-based model designed for natural language processing tasks that operates directly on byte-level input rather than traditional tokenized text. It aims to improve language understanding across multiple languages and domains by avoiding tokenization issues.

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