Ziyang Liu

According to our database, Ziyang Liu authored at least 32 papers between 2018 and 2026.

Collaborative distances:

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

2026

Training-Free and Unbiased Graph Collaborative Filtering for Personalized Recommendations.

Ziyang Liu, Chaokun Wang, Cheng Wu, Leqi Zheng, Hao Feng, Hang Zhang

IEEE Trans. Knowl. Data Eng., May, 2026

What Should I Cite? A RAG Benchmark for Academic Citation Prediction.

Leqi Zheng, Jiajun Zhang, Canzhi Chen, Chaokun Wang, Hongwei Li, Yuying Li, Yaoxin Mao, Shannan Yan, Zixin Song, Zhiyuan Feng, Zhaolu Kang, Zirong Chen, Hang Zhang, Qiang Liu, Liang Wang, Ziyang Liu

Proceedings of the ACM Web Conference 2026, 2026

2025

Pone-GNN: Integrating Positive and Negative Feedback in Graph Neural Networks for Recommender Systems.

Ziyang Liu, Chaokun Wang, Shuwen Zheng, Cheng Wu, Kai Zheng, Yang Song, Na Mou

Trans. Recomm. Syst., June, 2025

PLForge: Enhancing Language Models for Natural Language to Procedural Extensions of SQL.

Hang Zhang, Chaokun Wang, Hongwei Li, Cheng Wu, Songyao Wang, Yabin Liu, Gengyuan Shi, Ziyang Liu

Proc. ACM Manag. Data, 2025

Balancing Self-Presentation and Self-Hiding for Exposure-Aware Recommendation Based on Graph Contrastive Learning.

Leqi Zheng, Chaokun Wang, Ziyang Liu, Canzhi Chen, Cheng Wu, Hongwei Li

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Negative Feedback Really Matters: Signed Dual-Channel Graph Contrastive Learning Framework for Recommendation.

Leqi Zheng, Chaokun Wang, Zixin Song, Cheng Wu, Shannan Yan, Jiajun Zhang, Ziyang Liu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Effective and Scalable Heterogeneous Graph Neural Network Framework with Convolution-oriented Attention.

Ziqian Zhang, Chaokun Wang, Shuwen Zheng, Cheng Wu, Ziyang Liu, Hao Feng

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

Efficient Unsupervised Graph Embedding with Attributed Graph Reduction and Dual-Level Loss: (Extended Abstract).

Ziyang Liu, Chaokun Wang, Hao Feng, Ziyang Chen

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

LAGCL4Rec: When LLMs Activate Interactions Potential in Graph Contrastive Learning for Recommendation.

Leqi Zheng, Chaokun Wang, Canzhi Chen, Jiajun Zhang, Cheng Wu, Zixin Song, Shannan Yan, Ziyang Liu, Hongwei Li

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

TeRDy: Temporal Relation Dynamics through Frequency Decomposition for Temporal Knowledge Graph Completion.

Ziyang Liu, Chaokun Wang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Learning Multiple User Distributions for Recommendation via Guided Conditional Diffusion.

Cheng Wu, Liang Su, Chaokun Wang, Shaoyun Shi, Ziqian Zhang, Ziyang Liu, Wang Peng, Wenjin Wu, Peng Jiang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Efficient Unsupervised Graph Embedding With Attributed Graph Reduction and Dual-Level Loss.

Ziyang Liu, Chaokun Wang, Hao Feng, Ziyang Chen

IEEE Trans. Knowl. Data Eng., December, 2024

TeKo: Text-Rich Graph Neural Networks With External Knowledge.

Zhizhi Yu, Di Jin, Jianguo Wei, Yawen Li, Ziyang Liu, Yue Shang, Jiawei Han, Lingfei Wu

IEEE Trans. Neural Networks Learn. Syst., October, 2024

Enhancing Recommendation Accuracy and Diversity with Box Embedding: A Universal Framework.

Cheng Wu, Shaoyun Shi, Chaokun Wang, Ziyang Liu, Wang Peng, Wenjin Wu, Dongying Kong, Han Li, Kun Gai

Proceedings of the ACM on Web Conference 2024, 2024

Graph Contrastive Learning with Reinforcement Augmentation.

Ziyang Liu, Chaokun Wang, Cheng Wu

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Incorporating Dynamic Temperature Estimation into Contrastive Learning on Graphs.

Ziyang Liu, Chaokun Wang, Liqun Yang, Yunkai Lou, Hao Feng, Cheng Wu, Kai Zheng, Yang Song

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

GraphHI: Boosting Graph Neural Networks for Large-Scale Graphs.

Hao Feng, Chaokun Wang, Ziyang Liu, Yunkai Lou, Zhenyu Liu, Xiaokun Zhu, Yongjun Bao, Weipeng Yan

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Table Embedding Models Based on Contrastive Learning for Improved Cardinality Estimation.

Hongwei Li, Chaokun Wang, Ziyang Liu

Proceedings of the Web and Big Data - 8th International Joint Conference, 2024

2023

Embedding text-rich graph neural networks with sequence and topical semantic structures.

Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang, Hanghang Tong, Jiawei Han

Knowl. Inf. Syst., February, 2023

PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation.

Ziyang Liu, Chaokun Wang, Jingcao Xu, Cheng Wu, Kai Zheng, Yang Song, Na Mou, Kun Gai

CoRR, 2023

Graph Contrastive Learning with Generative Adversarial Network.

Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Fast Unsupervised Graph Embedding via Graph Zoom Learning.

Ziyang Liu, Chaokun Wang, Yunkai Lou, Hao Feng

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

TeKo: Text-Rich Graph Neural Networks with External Knowledge.

Zhizhi Yu, Di Jin, Jianguo Wei, Ziyang Liu, Yue Shang, Yun Xiao, Jiawei Han, Lingfei Wu

CoRR, 2022

Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search.

Ziyang Liu, Chaokun Wang, Hao Feng, Lingfei Wu, Liqun Yang

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: EMNLP 2022 - Industry Track, Abu Dhabi, UAE, December 7, 2022

2021

Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search.

Ziyang Liu, Zhaomeng Cheng, Yunjiang Jiang, Yue Shang, Wei Xiong, Sulong Xu, Bo Long, Di Jin

CoRR, 2021

BiTe-GCN: A New GCN Architecture via Bidirectional Convolution of Topology and Features on Text-Rich Networks.

Di Jin, Xiangchen Song, Zhizhi Yu, Ziyang Liu, Heling Zhang, Zhaomeng Cheng, Jiawei Han

Proceedings of the WSDM '21, 2021

AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich Networks.

Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang, Hanghang Tong, Jiawei Han

Proceedings of the IEEE International Conference on Data Mining, 2021

2020

BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks.

Di Jin, Xiangchen Song, Zhizhi Yu, Ziyang Liu, Heling Zhang, Zhaomeng Cheng, Jiawei Han

CoRR, 2020

NF-VGA: Incorporating Normalizing Flows into Graph Variational Autoencoder for Embedding Attribute Networks.

Hongyu Shan, Di Jin, Pengfei Jiao, Ziyang Liu, Bingyi Li, Yuxiao Huang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search.

Yunjiang Jiang, Yue Shang, Ziyang Liu, Hongwei Shen, Yun Xiao, Wei Xiong, Sulong Xu, Weipeng Yan, Di Jin

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks.

Di Jin, Ziyang Liu, Weihao Li, Dongxiao He, Weixiong Zhang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Robust Detection of Communities with Multi-semantics in Large Attributed Networks.

Di Jin, Ziyang Liu, Dongxiao He, Bogdan Gabrys, Katarzyna Musial

Proceedings of the Knowledge Science, Engineering and Management, 2018