AI RESEARCH
Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning
arXiv CS.LG
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ArXi:2506.05985v3 Announce Type: replace A generalist agent must continuously learn and adapt throughout its lifetime, achieving efficient forward transfer while minimizing catastrophic forgetting. Previous work within the dominant pretrain-then-finetune paradigm has explored parameter-efficient fine-tuning for single-task adaptation, effectively steering a frozen pretrained model with a small number of parameters.