GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation

ArXi:2511.00097v2 Announce Type: replace-cross Graph incremental learning (GIL), which continuously updates graph models by sequential knowledge acquisition, has garnered significant interest recently. However, existing GIL approaches focus on task-incremental and class-incremental scenarios within a single domain. Graph domain-incremental learning (Domain-IL), aiming at updating models across multiple graph domains, has become critical with the development of graph foundation models (GFMs), but remains unexplored in the literature.