Kuntharrgyal Khysru

DNFormer: Differential Attention for Graph Transformers

Graph Transformers (GTs) have emerged as a powerful paradigm for graph representation learning, leveraging attention mechanisms to enable flexible information exchange. Recent GTs often adopt local attention to restrict computation to neighborhoods, thereby reducing costs and enhancing scalability.