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Acacia is a graph foundation model trained exclusively on the Common Crawl web graph, supporting arbitrary features, various tasks like node classification and link prediction, and in-context learning without relying on pretrained LLMs.
AgentGFM proposes a graph foundation model where each node acts as an agent with a shared trainable policy, enabling adaptive information-flow control through a predict–act–observe–correct process. It achieves strong performance across node-level, graph-level, and large-scale transfer tasks.