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Gauge symmetries survive dimensional reduction intact: the classical BV pushforward rigorously preserves solutions to the classical master equation and their canonical equivalence classes.
A centralized model repository can enhance CSI feedback efficiency, achieving significant performance gains while slashing local training requirements.
Merging models for multi-task learning can be done without training, preserving task knowledge while minimizing interference through a focus on essential subspaces.
