GenRec combines page-wise NTP, token compression, and GRPO-SR reinforcement learning to scale generative retrieval, delivering 9.5% click and 8.7% transaction gains in production A/B tests on the JD App.
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cs.IR 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Data portability scenarios in algorithmic pluralism produce varying effects on user utility across different recommendation algorithms.
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GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation
GenRec combines page-wise NTP, token compression, and GRPO-SR reinforcement learning to scale generative retrieval, delivering 9.5% click and 8.7% transaction gains in production A/B tests on the JD App.
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Multistakeholder Impacts of Profile Portability in a Recommender Ecosystem
Data portability scenarios in algorithmic pluralism produce varying effects on user utility across different recommendation algorithms.