Personalized image generation aims to synthesize target images tailored to individual preferences based on users’ historical interaction data. Existing methods typically inject features from historical interaction records to guide personalized generation. However, such methods encounter two critical challenges when ser...
Yu-Ting Zhang, Ying Sun, Da-Zhong Shen et al.· Proceedings of the 20th ACM...· 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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