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Kuaishou Technology
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Aligning LLM reasoning with a dedicated recommendation head via reinforcement learning yields state-of-the-art recommendation performance in real-world systems.
Ditch rigid distribution assumptions: a novel residual quantization approach predicts continuous values by recursively refining quantization codes, outperforming SOTA in recommendation tasks.
