Text-Attributed Graphs (TAGs) are prevalent in various real-world scenarios, where each node is associated with a text attribute. Representation learning on TAGs relies on a comprehensive understanding of both the textual attributes and the topological connections. Recent works have enhanced graph neural networks (GNNs...
Hao Yan, Chao-Zhuo Li, Jun Yin et al.· ACM Transactions on Intellig...· 0 citations
This paper proposes the End-to-End Dual Dynamic (ED2) recommender, the first LLM-based sequential RS which adopts dual dynamic index mechanism, targeting resolving the above limitations simultaneously.
Jun Yin, Zhengxin Zeng, Mingzheng Li et al.· The Web Conference· 27 citations
This work introduces HybridSparse, an end-to-end hybrid retrieval framework that strengthens sparse--dense interaction across modeling, training, and serving and adopts a unified encoder with a shared backbone and jointly optimizes lexical and semantic representations through co-training.
Haotong Bao, Jianjin Zhang, Weihao Han et al.· Annual International ACM SIG...· 0 citations
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