Training Graph Foundation Models on The Web Graph

The paper introduces Acacia, a graph foundation model trained on the Common Crawl web graph. Acacia can handle arbitrary feature dimensionalities and semantics, perform node classification, link prediction, node clustering, and graph generation, and exhibit in-context learning—all without additional training or pretrained LLMs. Unlike existing models that require extra heads or rely on LLMs, Acacia is trained from scratch and can adapt to new graphs and labels directly.

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