Liangwei Yang

According to our database, Liangwei Yang authored at least 56 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models.

Rithesh Murthy, Ming Zhu, Liangwei Yang, Jielin Qiu, Juntao Tan, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang

CoRR, July, 2025

SGCL: Unifying Self-Supervised and Supervised Learning for Graph Recommendation.

Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Yuanjie Zhu, Philip S. Yu

CoRR, July, 2025

From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents.

Weizhi Zhang, Yangning Li, Yuanchen Bei, Junyu Luo, Guancheng Wan, Liangwei Yang, Chenxuan Xie, Yuyao Yang, Wei-Chieh Huang, Chunyu Miao, Henry Peng Zou, Xiao Luo, Yusheng Zhao, Yankai Chen, Chunkit Chan, Peilin Zhou, Xinyang Zhang, Chenwei Zhang, Jingbo Shang, Ming Zhang, Yangqiu Song, Irwin King, Philip S. Yu

CoRR, June, 2025

PersonaAgent: When Large Language Model Agents Meet Personalization at Test Time.

Weizhi Zhang, Xinyang Zhang, Chenwei Zhang, Liangwei Yang, Jingbo Shang, Zhepei Wei, Henry Peng Zou, Zijie Huang, Zhengyang Wang, Yifan Gao, Xiaoman Pan, Lian Xiong, Jingguo Liu, Philip S. Yu, Xian Li

CoRR, June, 2025

Masked Language Models are Good Heterogeneous Graph Generalizers.

Jinyu Yang, Cheng Yang, Shanyuan Cui, Zeyuan Guo, Liangwei Yang, Muhan Zhang, Chuan Shi

CoRR, June, 2025

Entropy-Based Block Pruning for Efficient Large Language Models.

Liangwei Yang, Yuhui Xu, Juntao Tan, Doyen Sahoo, Silvio Savarese, Caiming Xiong, Huan Wang, Shelby Heinecke

CoRR, April, 2025

RAU: Towards Regularized Alignment and Uniformity for Representation Learning in Recommendation.

Xi Wu, Dan Zhang, Chao Zhou, Liangwei Yang, Tianyu Lin, Jibing Gong

CoRR, March, 2025

LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation.

Weizhi Zhang, Liangwei Yang, Wooseong Yang, Henry Peng Zou, Yuqing Liu, Ke Xu, Sourav Medya, Philip S. Yu

CoRR, March, 2025

PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data.

Juntao Tan, Liangwei Yang, Zuxin Liu, Zhiwei Liu, Rithesh Murthy, Tulika Manoj Awalgaonkar, Jianguo Zhang, Weiran Yao, Ming Zhu, Shirley Kokane, Silvio Savarese, Huan Wang, Caiming Xiong, Shelby Heinecke

CoRR, February, 2025

Training Large Recommendation Models via Graph-Language Token Alignment.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

CoRR, February, 2025

Benchmarking LLMs for Political Science: A United Nations Perspective.

Yueqing Liang, Liangwei Yang, Chen Wang, Congying Xia, Rui Meng, Xiongxiao Xu, Haoran Wang, Ali Payani, Kai Shu

CoRR, February, 2025

Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap.

Weizhi Zhang, Yuanchen Bei, Liangwei Yang, Henry Peng Zou, Peilin Zhou, Aiwei Liu, Yinghui Li, Hao Chen, Jianling Wang, Yu Wang, Feiran Huang, Sheng Zhou, Jiajun Bu, Allen Lin, James Caverlee, Fakhri Karray, Irwin King, Philip S. Yu

CoRR, January, 2025

Diversified recommendation with weighted hypergraph embedding: Case study in music.

Chaoguang Luo, Liuying Wen, Yong Qin, Philip S. Yu, Liangwei Yang, Zhineng Hu

Neurocomputing, 2025

Training Large Recommendation Models via Graph-Language Tokens Alignment.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation Systems.

Yuwei Cao, Liangwei Yang, Zhiwei Liu, Yuqing Liu, Chen Wang, Yueqing Liang, Hao Peng, Philip S. Yu

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Taxonomy-Guided Zero-Shot Recommendations with LLMs.

Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, Kai Shu

Proceedings of the 31st International Conference on Computational Linguistics, 2025

PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data.

Juntao Tan, Liangwei Yang, Zuxin Liu, Zhiwei Liu, Rithesh R. N., Tulika Manoj Awalgaonkar, Jianguo Zhang, Weiran Yao, Ming Zhu, Shirley Kokane, Silvio Savarese, Huan Wang, Caiming Xiong, Shelby Heinecke

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

SpecTool: A Benchmark for Characterizing Errors in Tool-Use LLMs.

Shirley Kokane, Ming Zhu, Tulika Awalgaonkar, Jianguo Zhang, Thai Hoang, Akshara Prabhakar, Zuxin Liu, Tian Lan, Liangwei Yang, Juntao Tan, Rithesh Murthy, Weiran Yao, Zhiwei Liu, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong, Silvio Savarese

CoRR, 2024

PRACT: Optimizing Principled Reasoning and Acting of LLM Agent.

Zhiwei Liu, Weiran Yao, Jianguo Zhang, Rithesh Murthy, Liangwei Yang, Zuxin Liu, Tian Lan, Ming Zhu, Juntao Tan, Shirley Kokane, Thai Hoang, Juan Carlos Niebles, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong

CoRR, 2024

Personalized Multi-task Training for Recommender System.

Liangwei Yang, Zhiwei Liu, Jianguo Zhang, Rithesh Murthy, Shelby Heinecke, Huan Wang, Caiming Xiong, Philip S. Yu

CoRR, 2024

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets.

Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley Kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh Murthy, Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong

CoRR, 2024

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases.

Rithesh Murthy, Liangwei Yang, Juntao Tan, Tulika Manoj Awalgaonkar, Yilun Zhou, Shelby Heinecke, Sachin Desai, Jason Wu, Ran Xu, Sarah Tan, Jianguo Zhang, Zhiwei Liu, Shirley Kokane, Zuxin Liu, Ming Zhu, Huan Wang, Caiming Xiong, Silvio Savarese

CoRR, 2024

Mixed Supervised Graph Contrastive Learning for Recommendation.

Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Yuanjie Zhu, Philip S. Yu

CoRR, 2024

Against Filter Bubbles: Diversified Music Recommendation via Weighted Hypergraph Embedding Learning.

Chaoguang Luo, Liuying Wen, Yong Qin, Liangwei Yang, Zhineng Hu, Philip S. Yu

CoRR, 2024

AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System.

Zhiwei Liu, Weiran Yao, Jianguo Zhang, Liangwei Yang, Zuxin Liu, Juntao Tan, Prafulla Kumar Choubey, Tian Lan, Jason Wu, Huan Wang, Shelby Heinecke, Caiming Xiong, Silvio Savarese

CoRR, 2024

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning.

Jianguo Zhang, Tian Lan, Rithesh Murthy, Zhiwei Liu, Weiran Yao, Juntao Tan, Thai Hoang, Liangwei Yang, Yihao Feng, Zuxin Liu, Tulika Manoj Awalgaonkar, Juan Carlos Niebles, Silvio Savarese, Shelby Heinecke, Huan Wang, Caiming Xiong

CoRR, 2024

Cyclic Neural Network.

Liangwei Yang, Hengrui Zhang, Zihe Song, Jiawei Zhang, Weizhi Zhang, Jing Ma, Philip S. Yu

CoRR, 2024

Unified Pretraining for Recommendation via Task Hypergraphs.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Knowledge Graph Context-Enhanced Diversified Recommendation.

Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Instruction-based Hypergraph Pretraining.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Conditional Denoising Diffusion for Sequential Recommendation.

Yu Wang, Zhiwei Liu, Liangwei Yang, Philip S. Yu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets.

Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley Kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh R. N., Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation.

Chen Wang, Ziwei Fan, Liangwei Yang, Mingdai Yang, Xiaolong Liu, Zhiwei Liu, Philip S. Yu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Collaborative Alignment for Recommendation.

Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation.

Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Liancheng Fang, Philip S. Yu

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Personalized Multi-task Training for Recommender System.

Liangwei Yang, Zhiwei Liu, Jianguo Zhang, Rithesh Murthy, Shelby Heinecke, Huan Wang, Caiming Xiong, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2024

2023

Collaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language Model.

Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu

CoRR, 2023

Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation.

Yuwei Cao, Liangwei Yang, Chen Wang, Zhiwei Liu, Hao Peng, Chenyu You, Philip S. Yu

CoRR, 2023

Graph-based Village Level Poverty Identification.

Jing Ma, Liangwei Yang, Qiong Feng, Weizhi Zhang, Philip S. Yu

Proceedings of the ACM Web Conference 2023, 2023

DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation.

Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation.

Yuwei Cao, Liangwei Yang, Chen Wang, Zhiwei Liu, Hao Peng, Chenyu You, Philip S. Yu

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Graph-based Alignment and Uniformity for Recommendation.

Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering.

Xi Wu, Liangwei Yang, Jibing Gong, Chao Zhou, Tianyu Lin, Xiaolong Liu, Philip S. Yu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Dual-Teacher Knowledge Distillation for Strict Cold-Start Recommendation.

Weizhi Zhang, Liangwei Yang, Yuwei Cao, Ke Xu, Yuanjie Zhu, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2023

Multi-View Graph Convolution for Participant Recommendation.

Xiaolong Liu, Liangwei Yang, Chen Wang, Mingdai Yang, Zhiwei Liu, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2023

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation.

Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Federated Social Recommendation with Graph Neural Network.

Zhiwei Liu, Liangwei Yang, Ziwei Fan, Hao Peng, Philip S. Yu

ACM Trans. Intell. Syst. Technol., 2022

Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network.

Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu

CoRR, 2022

Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network.

Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation.

Yu Wang, Hengrui Zhang, Zhiwei Liu, Liangwei Yang, Philip S. Yu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System.

Shen Wang, Liangwei Yang, Jibing Gong, Shaojie Zheng, Shuying Du, Zhiwei Liu, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2022

2021

ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation.

Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma, Philip S. Yu

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

2020

Influential Nodes Identification in Complex Networks via Information Entropy.

Chungu Guo, Liangwei Yang, Xiao Chen, Duanbing Chen, Hui Gao, Jing Ma

Entropy, 2020

Approximation Algorithm for Shortest Path in Large Social Networks.

Dennis Nii Ayeh Mensah, Hui Gao, Liang Wei Yang

Algorithms, 2020