Achieving fairness in machine learning models while maintaining high accuracy is an important but complex task, especially when handling multiple sensitive attributes. Traditional fairness methods often struggle to eliminate bias within subgroups divided by sensitive attributes. Several key challenges have been identif...
Heng-Yu Yue, Fan Wang, Wei-Ming Liu et al.· Proceedings of the Thirty-Fi...· 0 citations
Dual-Entropy Enhanced Policy Optimization (DEEPO), a dual-stage enhancement combining signal variance regularization with gradient preconditioning with semantic-entropy-triggered expert prefixes inject grounded continuations on high-uncertainty queries, providing direct supervision and restoring advantage variance.
Ying-Xuan Zhuang, Miao Pan, Wang-Jie Gan et al.· 0 citations
ReSOT is proposed, a unified framework that Re-balances Semantic ID learning via Optimal Transport for GR and provides a principled tokenization scheme that preserves relational structure while assigning codes in a collision-aware and semantics-consistent manner.
Renwu Geng, Yi-Ming Xu, Fengxin Li et al.· Proceedings of the 32nd ACM...· 0 citations
Generative recommendation (GR) reformulates sequential recommendation as an autoregressive generation problem, where items are represented as discrete semantic IDs. However, learning effective item tokenization is critical yet remains challenging. Most existing methods optimize tokenization in a point-wise or heuristic...
Renwu Geng, Yiming Xu, Fengxin Li et al.· Proceedings of the 32nd ACM...· 0 citations
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