AINeutralarXiv – CS AI · 5h ago6/10
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On the importance of multiple training seeds for evaluating machine unlearning
A new study reveals that evaluating machine unlearning algorithms requires multiple training seeds, not just multiple unlearning seeds from a single trained model, as unlearning performance varies significantly based on initial training conditions. This finding challenges current evaluation practices in machine unlearning research across image classification, federated learning, and large language models.