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HKU Open Source OpenGraph: Overcoming the Difficulties of Graph Basic Models and Implementing a Multi-Domain Universal Graph Model
Recently, the University of Hong Kong has released OpenGraph, a breakthrough achievement that successfully overcomes three major challenges in the field of graph-based modeling. The model achieves zero-sample learning through clever techniques that can be adapted to a variety of downstream tasks.The construction of OpenGraph is divided into three main parts: a unified graph Tokenizer, an extensible graph Transformer, and knowledge distillation for large language models. OpenGraph solves the problem of variation in node set and feature space between different datasets by creating a unified graph Tokenizer. A topology-aware mapping approach is used ...- 4.5k
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