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Decentralized robotics data can yield stronger manipulation policies than centralized training: slotting locally trained client LoRAs directly into a server MoE beats centralized PEFT on real hardware by 12.23% while slashing communication by 87%.
Achieve strong, controllable privacy in federated biomedical AI without sacrificing performance, thanks to a lightweight key-embedded implicit neural representation.
