Artificial Intelligence


Breaking the Curse of Quality Saturation with User-Centric Ranking

we introduce an alternative formulation called “user-centric ranking” based on a transposed view, which casts ‘users’ as ‘tokens’ and ‘items’ as ‘documents’ instead. We show that this formulation has a number of advantages and shows less sign of quality saturation when trained on substantially larger data sets.


IMAGEBIND: One Embedding Space To Bind Them All

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