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Static labels in medical AI are giving way to dynamic models that can simulate disease evolution and guide personalized interventions.
eMoT achieves 100% accuracy on the Game of 24 by evolving reasoning as dynamic memories, outperforming traditional models by up to 17.6%.
Foundation models struggle with spatial tasks, achieving only 12% success in reproducing target viewpoints, but a novel post-training framework boosts performance to over 51%.
Singing deepfakes are a surprisingly effective attack vector, and this paper introduces a new benchmark and detection method to address the resulting security gap.
