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Adapts models to new data distributions during inference. Enhances model robustness and performance in changing environments.
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 Neural Collapse in Test-Time Adaptation Xiao Chen Zhongjing Du Jiazhen Huang Xu Jiang Li Lu Jingyan Jiang Zhi Wang | |||
 Instance-Aware Test-Time Segmentation for Continual Domain Shifts Seunghwan Lee Inyoung Jung Hojoon Lee Eunil Park Sungeun Hong | |||
 Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood Gilhyun Nam Taewon Kim Joonhyun Jeong Eunho Yang | |||
 Bridging Modalities via Progressive Re-alignment for Multimodal Test-Time Adaptation Jiacheng Li Songhe Feng | |||
 Uncover and Unlearn Nuisances: Agnostic Fully Test-Time AdaptationMachine-mediated learning (ML), 2025 | |||
 COLA: Context-aware Language-driven Test-time AdaptationIEEE Transactions on Image Processing (IEEE TIP), 2025 | |||
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