Author

Weinan Zhang

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Preprint Aug 2026

Learning from Unreachable Rewards: Hint-Conditioned Reinforcement Learning for Generative Recommendation

This work proposes Hint-Conditioned Generative Recommendation (HCGRec), a semantic-ID generative recommendation framework that recovers learning signal for such hard training instances and introduces hint-aware credit decomposition, using supervised learning to preserve item-semantic and prefix-structure alignment for hinted tokens and GRPO to optimize the sampled suffix.

Kangning Zhang, Hao Fang, Xukun Luo et al. · 0 citations

Book Open access Apr 2026

Modular Representation Compression: Adapting LLM Representations for Efficient and Effective Recommendation

Modular Representation Compression (MARC) is proposed to explicitly control the modularity of LLMs, and identifies a counterintuitive phenomenon during representation compression: Mid-layer Representation Advantage (MRA), where representations from middle layers of LLMs outperform those from final layers in recommendation tasks.

Yunjia Xi, Menghui Zhu, Jianghao Lin et al. · Annual International ACM SIG... · 0 citations