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cs.IR2026
Escaping the Euclidean Void: Manifold-Informed Flow Matching for Sequential Recommendation
Dengzhao Fang, Jingtong Gao, Yu Li +2
Conventional recommenders capture users' preferences by optimizing observed user-item relations, whereas continuous generative recommendation additionally learns the trajectory of…
cs.IR2026
PRISM: Purified Representation and Integrated Semantic Modeling for Generative Sequential Recommendation
Dengzhao Fang, Jingtong Gao, Yu Li +2
Generative Sequential Recommendation (GSR) has emerged as a promising paradigm, reframing recommendation as an autoregressive sequence generation task over discrete Semantic IDs (S…
cs.IR2025
HiD-VAE: Interpretable Generative Recommendation via Hierarchical and Disentangled Semantic IDs
Dengzhao Fang, Jingtong Gao, Chengcheng Zhu +3
Recommender systems are indispensable for helping users navigate the immense item catalogs of modern online platforms. Recently, generative recommendation has emerged as a promisin…