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LLMs can now autonomously learn to self-improve at test-time, nearly doubling utility by intelligently selecting and applying TTT strategies.
Up to 78 percentage points of reported machine unlearning success can be reversed with just 10 unlabeled images and zero weight updates, exposing widely cited forgetting benchmarks as mere BatchNorm illusions.