AI RESEARCH
GoTTA be Diverse: Rethinking Memory Policies for Test-Time Adaptation
arXiv CS.CV
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ArXi:2605.19890v1 Announce Type: new Test-time adaptation (TTA) enables a pre-trained model to adapt online to an unlabeled test stream under distribution shift. While most TTA research focuses on the adaptation objective, practical streams also depend critically on the memory used to select which test samples drive adaptation. Existing memory mechanisms are usually evaluated as components of specific TTA algorithms, making it difficult to isolate which memory design choices matter and when they matter.