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20232026
most citedEnhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck

67 citations · 88 across the 13 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.IR2026

Reward Guided Decoding for Generative Recommendation

Ruochen Yang, Yusheng Huang, Youfeng Zheng +11

Generative recommendation formulates recommendation task into an SID sequence autoregressive generation paradigm, but the decoding process is often dominated by generation likeliho…

cs.IR2026

Unifying Generative Recall and Multi-Objective Ranking in a Single Decoder-Only Sequence

Ruochen Yang, Shuang Wen, Pengbo Xu +6

Modern industrial recommendation systems typically separate recall and ranking into two independent stages. Although this cascade supports corpus-level retrieval and fine-grained m…

cs.IR2026★ 1 cited

Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users

Xiaodong Li, Jiawei Sheng, Jiangxia Cao +6

Cross-domain recommendation (CDR) has demonstrated to be an effective solution for alleviating the user cold-start issue. By leveraging rich user-item interactions available in a r…

cs.IR2026

S2CDR: Smoothing-Sharpening Process Model for Cross-Domain Recommendation

Xiaodong Li, Juwei Yue, Xinghua Zhang +5

User cold-start problem is a long-standing challenge in recommendation systems. Fortunately, cross-domain recommendation (CDR) has emerged as a highly effective remedy for the user…

cs.IR2026

From Agnostic to Specific: Latent Preference Diffusion for Multi-Behavior Sequential Recommendation

Ruochen Yang, Xiaodong Li, Jiawei Sheng +6

Multi-behavior sequential recommendation (MBSR) aims to learn the dynamic and heterogeneous interactions of users' multi-behavior sequences, so as to capture user preferences under…