Zheng Zhang

According to our database, Zheng Zhang authored at least 22 papers between 2022 and 2025.

Collaborative distances:

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

2025

CG-RAG: Research Question Answering by Citation Graph Retrieval-Augmented LLMs.

Yuntong Hu, Zhihan Lei, Zhongjie Dai, Allen Zhang, Abhinav Angirekula, Zheng Zhang, Liang Zhao

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

GRAG: Graph Retrieval-Augmented Generation.

Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, Liang Zhao

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

GraphNarrator: Generating Textual Explanations for Graph Neural Networks.

Bo Pan, Zhen Xiong, Guanchen Wu, Zheng Zhang, Yifei Zhang, Yuntong Hu, Liang Zhao

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

2024

TAGExplainer: Narrating Graph Explanations for Text-Attributed Graph Learning Models.

Bo Pan, Zhen Xiong, Guanchen Wu, Zheng Zhang, Yifei Zhang, Liang Zhao

CoRR, 2024

HiReview: Hierarchical Taxonomy-Driven Automatic Literature Review Generation.

Yuntong Hu, Zhuofeng Li, Zheng Zhang, Chen Ling, Raasikh Kanjiani, Boxin Zhao, Liang Zhao

CoRR, 2024

TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations.

Zheng Zhang, Yuntong Hu, Bo Pan, Chen Ling, Liang Zhao

CoRR, 2024

Link Prediction on Textual Edge Graphs.

Chen Ling, Zhuofeng Li, Yuntong Hu, Zheng Zhang, Zhongyuan Liu, Shuang Zheng, Liang Zhao

CoRR, 2024

Position-Aware Parameter Efficient Fine-Tuning Approach for Reducing Positional Bias in LLMs.

Zheng Zhang, Fan Yang, Ziyan Jiang, Zheng Chen, Zhengyang Zhao, Chengyuan Ma, Liang Zhao, Yang Liu

CoRR, 2024

Non-Euclidean Spatial Graph Neural Network.

Zheng Zhang, Sirui Li, Jingcheng Zhou, Junxiang Wang, Abhinav Angirekula, Allen Zhang, Liang Zhao

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Self-Similar Graph Neural Network for Hierarchical Graph Learning.

Zheng Zhang, Liang Zhao

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs.

Zhuofeng Li, Zixing Gou, Xiangnan Zhang, Zhongyuan Liu, Sirui Li, Yuntong Hu, Chen Ling, Zheng Zhang, Liang Zhao

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

Representation Learning of Geometric Trees.

Zheng Zhang, Allen Zhang, Ruth Nelson, Giorgio A. Ascoli, Liang Zhao

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

Transferable Unsupervised Outlier Detection Framework for Human Semantic Trajectories.

Zheng Zhang, Hossein Amiri, Dazhou Yu, Yuntong Hu, Liang Zhao, Andreas Züfle

Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

Distilling Large Language Models for Text-Attributed Graph Learning.

Bo Pan, Zheng Zhang, Yifei Zhang, Yuntong Hu, Liang Zhao

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

2023

Transferable Deep Clustering Model.

Zheng Zhang, Liang Zhao

CoRR, 2023

Balancing Specialized and General Skills in LLMs: The Impact of Modern Tuning and Data Strategy.

Zheng Zhang, Chen Zheng, Da Tang, Ke Sun, Yukun Ma, Yingtong Bu, Xun Zhou, Liang Zhao

CoRR, 2023

Beyond Text: A Deep Dive into Large Language Models' Ability on Understanding Graph Data.

Yuntong Hu, Zheng Zhang, Liang Zhao

CoRR, 2023

Large Language Models for Spatial Trajectory Patterns Mining.

Zheng Zhang, Hossein Amiri, Zhenke Liu, Andreas Züfle, Liang Zhao

CoRR, 2023

Tutorials at The Web Conference 2023.

Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne R. Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First.

Zheng Zhang, Junxiang Wang, Liang Zhao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unsupervised Deep Subgraph Anomaly Detection (Extended Abstract).

Zheng Zhang, Liang Zhao

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Unsupervised Deep Subgraph Anomaly Detection.

Zheng Zhang, Liang Zhao

Proceedings of the IEEE International Conference on Data Mining, 2022