AIBullisharXiv – CS AI · 14h ago7/10
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LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation
LoopFM introduces a novel knowledge distillation framework that transfers rich intermediate representations from large foundation models to compact vertical models, achieving significant conversion improvements (0.5-1.22%) in industrial-scale systems by structuring FM embeddings as input features rather than relying on single scalar predictions.