Feilong Tang

HeSRN: Representation Learning On Heterogeneous Graphs via Slot-Aware Retentive Network

2025 · arXiv (Cornell University)

Graph Transformers have recently achieved remarkable progress in graph representation learning by capturing long-range dependencies through self-attention. However, their quadratic computational complexity and inability to effectively model heterogeneous semantics severely limit their scalability and generalization …