DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts
arXiv:2605.12998v2 Announce Type: replace
Abstract: Continual graph learning (CGL) aims to learn from dynamically evolving graphs while mitigating catastrophic forgetting. Existing CGL approaches typically adopt a task-based formulation, where the dat…