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MedBN: Robust Test-Time Adaptation against Malicious Test Samples
In response to the emerging threat, we propose median batch normalization (MedBN), leveraging the robustness of the median for statistics estimation within the batch normalization layer during test-time inference.
Addressing Feature Imbalance in Sound Source Separation
Neural networks often suffer from a feature preference problem, where they tend to overly rely on specific features to solve a task while disregarding other features, even if those neglected features are essential for the task.
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