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Beyond Successor Accuracy: State Retention for Recursive Self-Improvement in Recommendation
Recommendation recursive self-improvement (Rec-RSI) feeds recommender outputs into subsequent training. Evaluating each round solely through its latest model assumes that the successor consolidates the update, although pre- and post-update models may retain complementary ranking decisions. We term t
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