This work presents UniGCRec, which constructs a cross-domain user profile from multi-domain histories and quantizes both users and items into CSC-IDs that integrate semantic and collaborative signals, effectively mitigating user-item asymmetry and enabling preference-aware selective transfer under low-overlap settings.
Chaoyue Ding, Jia-Hao Liu, Dongsheng Li et al.· Proceedings of the 32nd ACM...· 0 citations
By pre-training artificial neural networks exclusively on large-scale synthetic data, this work demonstrates robust zero-shot generalization across diverse brain regions, experimental paradigms and species, enabling the accurate inference of single-unit activities and cell-type properties without exposure to real data.
Cross-domain sequential recommendation (CDSR) improves target-domain prediction by leveraging multi-domain interaction histories. Most CDSR methods rely on shared entities or co-occurrence signals, which become unreliable when overlap is limited, and atomic ID representations further generalize poorly to long-tail or u...
Chaoyue Ding, Jiahao Liu, Dongsheng Li et al.· Proceedings of the 32nd ACM...· 0 citations
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