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School of Data Science and Engineering, East China Normal University, Shanghai, China
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Anomalies in text-attributed graphs can be detected more effectively by aligning textual semantics with graph topology, revealing insights that traditional methods overlook.
Skills tailored to specific LLM architectures can lead to a performance boost of nearly 26 points, challenging the notion of model-agnostic skill libraries.