Author

Tingwen Liu

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Jul 2026

Reward Guided Decoding for Generative Recommendation

Value-guided decoding is proposed, named RGD, a controllable decoding framework for industrial value-oriented generative recommendation that deriving a closed-form reward guided decoding distribution that principledly combines generation probability with reward signals.

Ruo-Chen Yang, Yu-Sheng Huang, Youfeng Zheng et al. · arXiv.org · 1 citation

Jul 2026

Unifying Generative Recall and Multi-Objective Ranking in a Single Decoder-Only Sequence

This work proposes UniR, a decoder-only Transformer that unifies Generative and Multi-Objective ranking within a single heterogeneous sequence comprising user context, SID trajectory, and item features, validating the practicality of unified model in large-scale recommendation systems.

Ruo-Chen Yang, Shuang Wen, Peng-Bo Xu et al. · arXiv.org · 1 citation