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Surprisingly, the "think before answer" paradigm fails to enhance generative recommendation models, prompting a novel approach that redefines how reasoning is integrated into these systems.
Task-oriented dialogue agents can now learn to balance user satisfaction and operational costs, thanks to a new RL framework that optimizes for both.
