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Transition effects can be disentangled into reusable primitives, leading to superior policy learning even in complex, ambiguous environments.
Achieve 13-15% more efficient LLM watermark detection by using e-values for anytime-valid inference, enabling early stopping without sacrificing statistical guarantees.
