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Zayed University of Arti- ficial Intelligence (MBZUAI), University of Buffalo. Correspon
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Standard attention mechanisms inevitably cause intertask interference in in-context continual learning, leading to systematic bias and performance degradation in long prompts.
ViTs can achieve robust generalization through adversarial training even when overfitting, mirroring a phenomenon previously observed only in CNNs.
