30 citations · 62 across the 10 of their papers we have counts for
7 papers · 1 filter
SNAP: Low-Latency Test-Time Adaptation with Sparse Updates
Hyeongheon Cha, Dong Min Kim, Hye Won Chung +2
Test-Time Adaptation (TTA) adjusts models using unlabeled test data to handle dynamic distribution shifts. However, existing methods rely on frequent adaptation and high computatio…
Test-Time Adaptation with Binary Feedback
Taeckyung Lee, Sorn Chottananurak, Junsu Kim +3
Deep learning models perform poorly when domain shifts exist between training and test data. Test-time adaptation (TTA) is a paradigm to mitigate this issue by adapting pre-trained…
AETTA: Label-Free Accuracy Estimation for Test-Time Adaptation
Taeckyung Lee, Sorn Chottananurak, Taesik Gong +1
Test-time adaptation (TTA) has emerged as a viable solution to adapt pre-trained models to domain shifts using unlabeled test data. However, TTA faces challenges of adaptation fail…
SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
Taesik Gong, Yewon Kim, Taeckyung Lee +2
Test-time adaptation (TTA) aims to address distributional shifts between training and testing data using only unlabeled test data streams for continual model adaptation. However, m…
IMG2IMU: Translating Knowledge from Large-Scale Images to IMU Sensing Applications
Hyungjun Yoon, Hyeongheon Cha, Hoang C. Nguyen +2
Pre-training representations acquired via self-supervised learning could achieve high accuracy on even tasks with small training data. Unlike in vision and natural language process…
NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation
Taesik Gong, Jongheon Jeong, Taewon Kim +3
Test-time adaptation (TTA) is an emerging paradigm that addresses distributional shifts between training and testing phases without additional data acquisition or labeling cost; on…
DAPPER: Label-Free Performance Estimation after Personalization for Heterogeneous Mobile Sensing
Taesik Gong, Yewon Kim, Adiba Orzikulova +4
Many applications utilize sensors in mobile devices and machine learning to provide novel services. However, various factors such as different users, devices, and environments impa…