The presence of noisy labels in a training dataset can significantly impact the performance of
machine learning models. To tackle this issue, researchers have explored methods for …

Deep neural networks often rely on spurious features, which are attributes correlated with
class labels but irrelevant to the actual task, leading to poor generalization when these …

Dataset bias, in the context of machine learning, pertains to the issue of unintended
correlations between target labels and undesirable features found in specific training …