Multi-Hypothesis Test-Time Adaptation to Mitigate Underspecification

arXiv cs.CV1mo4 min read

arXiv:2607.00259v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) seeks to improve model robustness under distribution shifts by adapting parameters using unlabeled target data. However, in the absence of supervision, entropy-based adaptation is fundamentally underconstrained: multiple distinct parameter updates can achieve similarly low entropy while inducing drastically different decision boundaries. This phenomenon, known as underspecification, renders standard TTA brittle and prone to collapse into spurious modes. In this work, we reinterpret TTA through a posterior-inspired lens

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Multi-Hypothesis Test-Time Adaptation to Mitigate Underspecification

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