“…• Data augmentation techniques such as data synthesis, data generation, or data simulation, to augment the available data and create synthetic data points for training unlearning models. Data augmentation can help overcome the challenge by generating additional training data, which can improve the effectiveness and generalizability of unlearning techniques [139], [205], [206].…”