Unverified50% confidenceFactExact time
Across the three datasets, none showed that edges accounted for most of the GNN's advantage over node-specific models.
1
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50%
Confidence
Long-term
Relevance
10/27/2026
First Seen
Sources
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Related Claims
UnverifiedOn the feeder data, parameter sharing recovers about two-thirds of the error gap between node-specific models and the GNN (relative to the regularized baseline).68% similarUnverified图神经网络（GNN）核心操作是消息传递，不同图卷积变体如GCN、GAT、GraphSAGE在不同任务上各有优劣65% similarUnverifiedGNNs address the problems in graph data of a non-fixed number of neighbors and meaningless ordering through the message passing mechanism: in each layer, a node first aggregates the feature information of its neighbors, then combines it with its own representation and updates it through a nonlinear transformation.65% similarUnverifiedGCD does not affect prediction utility or top-1 accuracy, because the rewriting only acts on the externally exposed query responses, and the model's internal inference logic is unchanged.60% similarUnverified表格数据缺乏局部相关性和序列结构，使得卷积和自注意力的归纳偏置优势难以发挥57% similar
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