Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned
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CHoE: Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned Experts
arXiv:2605.15888v2 Announce Type: replace Abstract: Heterogeneous Graph Prompt Learning (HGPL)has emerged as a promising paradigm for bridging the gap between the objectives of pre-training foundation models and their downstream applications in heterogeneous graph settings. However, existing HGPL methods are primarily designed for in-domain scenarios, whereas real-world deployments often span multiple domains, and the data used for pre-training and downstream tasks may originate from...