2 papers
cs.LG2026
NEO: No-Optimization Test-Time Adaptation through Latent Re-Centering
Alexander Murphy, Michal Danilowski, Soumyajit Chatterjee +1
Test-Time Adaptation (TTA) methods are often computationally expensive, require a large amount of data for effective adaptation, or are brittle to hyperparameters. Based on a theor…
cs.LG2025
BoTTA: Benchmarking on-device Test Time Adaptation
Michal Danilowski, Soumyajit Chatterjee, Abhirup Ghosh
The performance of deep learning models depends heavily on test samples at runtime, and shifts from the training data distribution can significantly reduce accuracy. Test-time adap…