AI RESEARCH
Stable Routing for Mixture-of-Experts in Class-Incremental Learning
arXiv CS.LG
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ArXi:2605.17571v1 Announce Type: cross Class-incremental learning (CIL) requires models to learn new classes sequentially while preserving prior knowledge. Recently, approaches that combine pre-trained models with mixture-of-experts (MoE) have received increasing attention in CIL: they typically expand experts during learning and employ a router to assign weights across experts. However, existing MoE methods often overlook routing drift induced by expert expansion. Once new experts are