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Curiosity-driven exploration can dramatically enhance policy personalization in federated learning, even in sparse-reward scenarios.
UnDA achieves superior cross-modal knowledge transfer in medical imaging, even in the absence of paired clinical data, by dynamically suppressing noise from uncertain predictions.
