AI RESEARCH
One Pool Is Not Enough: Multi-Cluster Memory for Practical Test-Time Adaptation
arXiv CS.AI
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ArXi:2603.21135v1 Announce Type: cross Test-time adaptation (TTA) adapts pre-trained models to distribution shifts at inference using only unlabeled test data. Under the Practical TTA (PTTA) setting, where test streams are temporally correlated and non-i.i.d., memory has become an indispensable component for stable adaptation, yet existing methods universally amples in a single unstructured pool.