class-incremental learning

When Generator Replay Degrades: Projected Rehearsal Orchestration for Heterogeneous Federated Class-Incremental Learning

A new arXiv preprint introduces PRO and PRO-MAX, frameworks that replace synthetic input replay with projected rehearsal orchestration to address degradation in federated class-incremental learning (FCIL) when clients have heterogeneous label subsets and task stages. The methods improve retention and utility across image, text, and graph benchmarks, showing that replay quantity alone does not resolve quality failures.