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Agents trained in this framework achieve unprecedented improvements in reasoning depth and citation accuracy, transforming the landscape of automated peer review processes.
Normalizing flows enable stable actor-critic learning for complex stochastic control problems with jumps, opening the door to more realistic financial and economic models.