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RecHarness boosts recommender system performance by over 2% in real-world applications while minimizing the need for manual engineering interventions.
Ditch rigid distribution assumptions: a novel residual quantization approach predicts continuous values by recursively refining quantization codes, outperforming SOTA in recommendation tasks.
