<ul><li>Graph Neural Networks (GNNs) are widely used in graph data mining tasks.</li><li>Traditional GNNs face limitations in the receptive field during message passing processes.</li><li>A new model called Tokenphormer utilizes fine-grained token-based representation learning to capture local and structural information.</li><li>Tokenphormer achieves state-of-the-art performance on node classification tasks.</li></ul>

Tokenphormer: Structure-aware Multi-token Graph Transformer for Node Classification

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