Generative recommendation has emerged as a promising direction in AI-driven recommendation systems, shifting from traditional scoring models to multi-step reasoning approaches. However, a critical question has remained unanswered: when a model performs latent reasoning in recommendation contexts, is it truly reasoning about user interests, or merely performing deeper feature transformations?Addressing this challenge, Fu Cong's team, in collabora…
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