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Controllable Generative Recommendation via Guided Token Refinement

Zhang, Haichao et al.
arXiv (All) · Papers
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i-2-6information-retrieval
Generative recommendation over discrete Semantic IDs has become a powerful paradigm for item retrieval. Real-world systems, however, frequently require real-time controllability to balance accuracy against objectives such as diversity. Existing autoregressive methods generate tokens strictly from le
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