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Forget one-size-fits-all preprocessing: the best way to encode numerical features for tabular deep learning hinges on the task, backbone, and even the output size.
Recommending popular items isn't always what users want: SPREE steers sequential models to align with individual users' preferences for popular or niche content, improving recommendations.
