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Shengcai Liu

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Towards Geometry-Aware Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization

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May 14, 2024
Yongfan Lu, Zixiang Di, Bingdong Li, Shengcai Liu, Hong Qian, Peng Yang, Ke Tang, Aimin Zhou

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Pointer Networks Trained Better via Evolutionary Algorithms

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Dec 06, 2023
Muyao Zhong, Shengcai Liu, Bingdong Li, Haobo Fu, Chao Qian, Ke Tang, Peng Yang

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Large Language Models as Evolutionary Optimizers

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Nov 01, 2023
Shengcai Liu, Caishun Chen, Xinghua Qu, Ke Tang, Yew-Soon Ong

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Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation

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Oct 15, 2023
Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang

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Dataset Condensation for Recommendation

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Oct 02, 2023
Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Rui He, Qing Li, Ke Tang

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Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling

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Sep 22, 2023
Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Qing Li, Ke Tang

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Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization

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Aug 27, 2023
Wenjie Chen, Shengcai Liu, Yew-Soon Ong, Ke Tang

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Data-Driven Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications

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Jun 26, 2023
Xuanfeng Li, Shengcai Liu, Jin Wang, Xiao Chen, Yew-Soon Ong, Ke Tang

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Large Language Models can be Guided to Evade AI-Generated Text Detection

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May 19, 2023
Ning Lu, Shengcai Liu, Rui He, Qi Wang, Ke Tang

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Multi-Domain Learning From Insufficient Annotations

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May 04, 2023
Rui He, Shengcai Liu, Jiahao Wu, Shan He, Ke Tang

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