tta

Test-time adaptation Test-time adaptation is one of the emerging topics in tackling distribution shift in model deployment. Typically, the lifecycle of the model deployment includes followings: (Pre)-Training the model on the training dataset offline. Deploying the model in real world After getting some more data, further retrain the model Repeat 2,3 steps Some of the issues with the above steps are: The environment might change during the deployment period, so the model might lose its performance over time....