Tail Cues, Principal Corrections: Plug-and-Play Rectification for Open-Set Test-Time Adaptation
Open-Set Test-Time Adaptation (OSTTA) operates on non-stationary target streams where covariate and semantic shifts coexist. Existing TTA methods often obtain adaptation signals by updating model parameters or maintaining mutable memories, which can be costly and vulnerable to unknown samples. We present TALOR, a lightweight, backward-free rectification module that uses the source linear head as a geometric anchor. The head-induced basis decomposes each normalized feature into high-gain principal coordinates and low-gain tail coordinates. TALOR estimates a soft-routed affine correction in the principal subspace, combining a regime-level principal bias with a tail-conditioned slope that ca...
| Authors | Yingkai Yang, Chaoqi Chen, Hui Huang |
|---|---|
| Primary category | cs.LG |
| Published | 27 October 2026 |
| Last updated at source | 27 October 2026 |
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