Paper-Conference

Diagnostic-Guided Dynamic Profile Optimization for LLM-based User Simulators in Sequential Recommendation
Hongyang Liu, Zhu Sun, Tianjun Wei, Yan Wang, Jiajie Zhu, Xinghua Qu
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Dynamic Experts Synergy for Multi-Task Recommendation
Haotian Wu, Yingpeng Du, Zhu Sun, Jie Zhang, Puay Siew Tan
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HyMoERec: Hybrid Mixture-of-Experts for Sequential Recommendation
Kunrong Li, Zhu Sun, Kwan Hui Lim
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ONE-PASS: Single Forward Pass Decoding for Listwise Reranking
Yingpeng Du, Tianjun Wei, Zhu Sun, Jie Zhang
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Orthogonal Meta-learning Boosted Bayesian Optimization for Uncertain Multi-Objective Recommendation
Hongxu Wang, Yingpeng Du, Zhu Sun, Lu Zhang, Tiantian He, Yew Soon Ong
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Reinforcement Speculative Decoding for Fast Ranking
Yingpeng Du, Tianjun Wei, Zhu Sun, Jie Zhang, Xun Jiang
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Active Large Language Model-based Knowledge Distillation for Session-based Recommendation
Large language models (LLMs) provide a promising way for accurate session-based recommendation (SBR), but they demand substantial …
Yingpeng Du, Zhu Sun, Ziyan Wang, Haoyan Chua, Jie Zhang, Yew-Soon Ong
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Enhancing New-item Fairness in Dynamic Recommender Systems
“New-items play a crucial role in recommender systems (RSs) for delivering fresh and engaging user experiences. However, …
Huizhong Guo, Zhu Sun, Dongxia Wang, Tianjun Wei, Jinfeng Li, Jie Zhang
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LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture
‘Recently, Graph Neural Networks (GNNs) have become the dominant approach for Knowledge Graph-aware Recommender Systems (KGRSs) …
Yanhui Li, Dongxia Wang, Zhu Sun, Haonan Zhang, Huizhong Guo
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LLM4RSR: Large Language Models as Data Correctors for Robust Sequential Recommendation
Sequential Recommenders (SRs) are trained to predict the next item as the target given its preceding items as the input, assuming every …
Yatong Sun, Xiaochun Yang, Zhu Sun, Yan Wang, Bin Wang, Xinghua Qu
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