Publications

Liangwei Yang, Shiyu Wang, Haolin Chen, Rithesh Murthy, Ming Zhu, Jielin Qiu, Zixiang Chen, Juntao Tan, Jianguo Zhang, Zhiwei Liu, Wenting Zhao, Silvio Savarese, Caiming Xiong, Huan Wang, Shelby Heinecke (2026). Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models. In ICML 2026.

Liangwei Yang, Yuhui Xu, Juntao Tan, Doyen Sahoo, Silvio Savarese, Caiming Xiong, Huan Wang, Shelby Heinecke (2026). Entropy-Based Block Pruning for Efficient Large Language Models. In ICLR 2026.

Weizhi Zhang, Liangwei Yang, Wooseong Yang, Henry Peng Zou, Yuqing Liu, Ke Xu, Sourav Medya, Philip S Yu (2025). Llminit: A free lunch from large language models for selective initialization of recommendation. In EMNLP 2025.

Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Yuanjie Zhu, Philip S. Yu (2025). Sgcl: Unifying self-supervised and supervised learning for graph recommendation. In RecSys 2025.

Juntao Tan, Liangwei Yang, Zuxin Liu, Zhiwei Liu, Rithesh RN, Tulika Manoj Awalgaonkar, Jianguo Zhang, Weiran Yao, Ming Zhu, Shirley Kokane, Silvio Savarese, Huan Wang, Caiming Xiong, Shelby Heinecke (2025). Personabench: Evaluating ai models on understanding personal information through accessing (synthetic) private user data. In ACL 2025.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu (2025). Training Large Recommendation Models via Graph-Language Tokens Alignment. In WWW 2025.

Yuwei Cao, Liangwei Yang, Zhiwei Liu, Yuqing Liu, Chen Wang, Yueqing Liang, Hao Peng, Philip S. Yu (2025). Graph-sequential alignment and uniformity: Toward enhanced recommendation systems. In WWW 2025.

Yueqing Liang, Liangwei Yang, Chen Wang, Congying Xia, Rui Meng, Xiongxiao Xu, Haoran Wang, Ali Payani, Kai Shu (2025). Benchmarking llms for political science: A united nations perspective. In AAAI 2026.

Chaoguang Luo, Liuying Wen, Yong Qin, Philip S. Yu, Liangwei Yang, Zhineng Hu (2025). Diversified recommendation with weighted hypergraph embedding: Case study in music. Neurocomputing.

Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, Kai Shu (2025). Taxonomy-guided zero-shot recommendations with llms. In COLING 2025.

Zhiwei Liu, Weiran Yao, Jianguo Zhang, Rithesh Murthy, Liangwei Yang, Zuxin Liu, Tian Lan, Ming Zhu, Juntao Tan, Et Al. (2024). PRACT: Optimizing Principled Reasoning and Acting of LLM Agent. In CONLL 2024.

Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh RN, Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong (2024). Apigen: Automated pipeline for generating verifiable and diverse function-calling datasets. In NIPS 2024.

Liangwei Yang, Zhiwei Liu, Jianguo Zhang, Rithesh Murthy, Shelbu Heinecke, Huan Wang, Caiming Xiong, Philip S. Yu (2024). Personalized Multi-task Training for Recommender System. In IEEE BigData 2024.

Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zhou, Ke Xu, Liancheng Fang, Philip S. Yu (2024). Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation. In CIKM 2024.

Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu (2024). Collaborative Alignment for Recommendation. In CIKM 2024.

Chen Wang, Ziwei Fan, Liangwei Yang, Mingdai Yang, Xiaolong Liu, Zhiwei Liu, Philip S. Yu (2024). Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation. In KDD 2024.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu (2024). Instruction-based Hypergraph Pretraining. In SIGIR 2024.

Yu Wang, Zhiwei Liu, Liangwei Yang, Philip S. Yu (2024). Conditional denoising diffusion for sequential recommendation. In PAKDD 2024.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu (2024). Unified Pretraining for Recommendation via Task Hypergraphsn. In WSDM 2024.

Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu (2024). Knowledge Graph Context-Enhanced Diversified Recommendation. In WSDM 2024.

Xiaolong Liu, Liangwei Yang, Chen Wang, Mingdai Yang, Zhiwei Liu, Philip S. Yu (2023). Multi-View Graph Convolution for Participant Recommendation. In IEEE BigData 2023.

Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu (2023). Group-Aware Interest Disentangled Dual-Training for Personalized Recommendationn. In IEEE BigData 2023.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu (2023). Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning. In CIKM 2023.

Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu (2023). Graph-based Alignment and Uniformity for Recommendation. In CIKM 2023.

Weizhi Zhang, Liangwei Yang, Yuwei Cao, Ke Xu, Yuanjie Zhu, Philip S. Yu (2023). Dual-Teacher Knowledge Distillation for Strict Cold-Start Recommendation. In IEEE BigData 2023.

Xi Wu, Liangwei Yang, Jibing Gong, Chao Zhou, Tianyu Lin, Xiaolong Liu, Philip S. Yu (2023). Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering. In CIKM 2023.

Jing Ma, Liangwei Yang, Qiong Feng, Weizhi Zhang, Philip S. Yu (2023). Graph-based Village Level Poverty Identification. In WWW 2023.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu (2023). Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph. In WSDM 2023.

Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang (2023). DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation. In WSDM 2023.

Liangwei Yang, Shen Wang, Jibing Gong, Shaojie Zheng, Shuying Du, Zhiwei Liu, Philip S. Yu (2022). MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System. In IEEE BigData 2022.

Jing Ma, Liangwei Yang, Zhineng Hu (2022). A Counterfactual Assessment of Poverty Alleviation Sustainability on Multiple Non-equivalent Household Groups. In Population Research and Policy Review.

Yu Wang, Hengrui Zhang, Zhiwei Liu, Liangwei Yang, Philip S. Yu (2022). ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation. In CIKM 2022.

Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu (2022). Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network. In WWW2022.

Zhiwei Liu, Liangwei Yang, Ziwei Fan, Hao Peng, Philip S. Yu (2022). Federated Social Recommendation with Graph Neural Network. In TIST.

Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma, Philip S. Yu (2021). ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation. In SIGIR 2021.

Chungu Guo, Liangwei Yang, Xiao Chen, Duanbing Chen, Hui Gao, Jing Ma (2020). Influential Nodes Identification in Complex Networks via Information Entropy. In Entropy.

Dennis Nii Ayeh Mensah, Hui Gao, Liangwei Yang (2019). Approximation Algorithm for Shortest Path in Large Social Networks. In Algorithms.

Liangwei Yang, Hui Gao, Keyu Wu, Haotian Zhang, Changyu Li, Lixia Tang (2019). Identification of Cancerlectins By Using Cascade Linear Discriminant Analysis and Optimal g-gap Tripeptide Composition. In Current Bioinformatics.

Zhineng Hu, Jing Ma, Liangwei Yang, Liming Yao, Meng Pang (2019). Monthly Electricity Demand Forecasting using Empirical Mode Decomposition-based State Space Model. In Energy & Environment.

Zhineng Hu, Jing Ma, Liangwei Yang, Xiaoping Li, Meng Pang (2019). Decomposition-Based Dynamic Adaptive Combination Forecasting for Monthly Electricity Demand. In Sustainability.

Liangwei Yang, Hui Gao, Zhen Liu, Lixia Tang (2018). Identification of Phage Virion Proteins by using the g-gap Tripeptide Composition. In Letters in Organic Chemistry.