Publication

Most up-to-date publications are here

Workshops

• Machine Learning on Graphs in the Era of Generative Artificial Intelligence
  [KDD 2025] ACM SIGKDD Conference on Knowledge Discovery & Data Mining
  Yu Wang, Yu Zhang, Zhichun Guo, Harry Shomer, Haoyu Han, Tyler Derr, Nesreen Ahmed, Mahantesh Halappanavar, Jiliang Tang
  [Website]

• SURGeLLM: Structured Understanding, Retrieval, and Generation in LLMs era
  [ACL 2026] Annual Meeting of the Association for Computational Linguistics
  Vivek Gupta, Kaize Ding, Harsha Kokel, Yue Zhao, Amit Agarwal, Yu Wang, Michael Glass, Yu Zhang, Kavitha Srinivas, Xiusi Chen, Oktie Hassanzadeh, Qi Zhu, Shuaichen Chang, Yuan Luo
  [Website]

Tutorials

• Rigorizing Retrieval-augmented Generation with Structural Intelligence
  [WSDM 2026] ACM International Conference on Web Search and Data Mining
  Zhisheng Qi, Yongjia Lei, Haoyu Han, Harry Shomer, Kaize Ding, Yu Zhang, Ryan Rossi, Hui Liu, Yu Wang
  [Website]

• Empowering Retrieval-augmented Generation with Graph-structured Knowledge
  [SDM 2025] SIAM International Conference on Data Mining
  Yu Wang, Haoyu Han, Harry Shomer, Kai Guo, Yongjia Lei, Jiayuan Ding, Xianfeng Tang, Qi He, Jiliang Tang
  [Website]

• Data Quality-Aware Graph Machine Learning
  [CIKM 2024] ACM International Conference on Information and Knowledge Management
  Yu Wang, Kaize Ding, Xiaorui Liu, Jian Kang, Ryan Rossi, Tyler Derr
  [Website]

• Data Quality-aware Graph Machine Learning
  [SDM 2024] SIAM International Conference on Data Mining
  Yu Wang, Yijun Tian, Tong Zhao, Xiaorui Liu, Jian Kang, Tyler Derr

Book Chapter

• Graph Neural Networks: Self-supervised Learning
  [Springer Nature] In Graph Neural Networks: Foundations, Frontiers, and Applications, Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao.
  Yu Wang, Wei Jin, Tyler Derr
  [Chapter][Book]

Conference/Journal Papers

• Building Transparency in Deep Learning-Powered Network Traffic Classification: A Traffic-Explainer Framework
  [KDD 2026] ACM SIGKDD Conference on Knowledge Discovery & Data Mining
  Riya Ponraj, Ram Durairajan, Yu Wang
  [Paper][Code]

• Rule Mining and Learning for Structured Knowledge Retrieval
  [WSDM 2026] ACM International Conference on Web Search and Data Mining
  Yongjia Lei, Mahantesh M Halappanavar, Yu Wang
  [Paper][Code]

• Knowledge Homophily in Large Language Models
  [WSDM 2026] ACM International Conference on Web Search and Data Mining
  Utkarsh Sahu, Zhisheng Qi, Mahantesh M Halappanavar, Nedim Lipka, Ryan A Rossi, Franck Dernoncourt, Yu Zhang, Yao Ma, Yu Wang
  [Paper][Code]

• Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases
  [ACL 2025] Annual Meeting of the Association for Computational Linguistics
  Yongjia Lei, Haoyu Han, Ryan A Rossi, Franck Dernoncourt, Nedim Lipka, Mahantesh M Halappanavar, Jiliang Tang, Yu Wang
  Best Poster Honorable Mention at SDM’25 Doctoral Forum
  [Paper][Code]

• Personalization of Large Language Models: A Survey
  [TMLR 2025] Transactions on Machine Learning Research
  Zhehao Zhang, Ryan A. Rossi, Branislav Kveton, Yijia Shao, Diyi Yang, Hamed Zamani, Franck Dernoncourt, Joe Barrow, Tong Yu, Sungchul Kim, Ruiyi Zhang, Jiuxiang Gu, Tyler Derr, Hongjie Chen, Junda Wu, Xiang Chen, Zichao Wang, Subrata Mitra, Nedim Lipka, Nesreen Ahmed, Yu Wang
  [Paper]

• SaVe-TAG: Semantic-aware Vicinal Risk Minimization for Long-Tailed Text-Attributed Graphs
  [KDD 2026] ACM SIGKDD Conference on Knowledge Discovery & Data Mining
  Leyao Wang, Yu Wang, Bo Ni, Yuying Zhao, Haoyu Wang, Yao Ma, Tyler Derr
  [Paper][Code]

• Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs
  [WWW 2026] In Proceedings of the ACM Web Conference
  Haoyu Han, Kai Guo, Harry Shomer, Yu Wang, Yucheng Chu, Hang Li, Li Ma, Jiliang Tang

• A Survey on LLM-based Conversational User Simulation
  [EACL 2026] Conference of European Chapter of Association for Computational Linguistics
  Bo Ni, Leyao Wang, Yu Wang, Yuying Zhao, Tyler Derr, Ryan A. Rossi

• From Selection to Generation: A Survey of LLM-based Active Learning
  [ACL 2025] Annual Meeting of the Association for Computational Linguistics
  Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, Junda Wu, Xintong Li, Ryan Aponte, Hanjia Lyu, Joe Barrow, Hongjie Chen, Franck Dernoncourt, Branislav Kveton, Tong Yu, Ruiyi Zhang, Jiuxiang Gu, Nesreen K. Ahmed, Yu Wang, Xiang Chen, Hanieh Deilamsalehy, Sungchul Kim, Zhengmian Hu, Yue Zhao, Nedim Lipka, Seunghyun Yoon, Ting-Hao Kenneth Huang, Zichao Wang, Puneet Mathur, Soumyabrata Pal, Koyel Mukherjee, Zhehao Zhang, Namyong Park, Thien Huu Nguyen, Jiebo Luo, Ryan A. Rossi, Julian McAuley

• Demystifying the Power of LLMs in Graph Generation
  [NAACL 2025] Nations of Americans Chapter of Association for Computational Linguistics
  Yu Wang, Ryan A Rossi, Namyong Park, Nesreen K Ahmed, Danai Koutra, Franck Dernoncourt, Tyler Derr
  [Paper][Code]

• Large Graph Generative Models
  [ICLR 2025] International Conference on Learning Representation
  Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr
  [Paper][Code]

• Edge Classification: New Directions in Topological Imbalance
  [WSDM 2025] ACM International Conference on Web Search and Data Mining
  Yu Wang*, Xueqi Cheng*, Yuying Zhao, Charu Aggarwal, Tyler Derr
  [Paper][Code]

• Empowering GraphRAG with Knowledge Filtering and Integration
  [EMNLP 2025] Empirical Methods in Natural Language Processing
  Kai Guo, Harry Shomer, Shenglai Zeng, Haoyu Han, Yu Wang, Jiliang Tang
  [Paper]

• DynaSaur: Large Language Agents Beyond Predefined Actions
  [COLM 2025] Second Conference on Language Modeling
  Dang Nguyen, Viet Dac Lai, Seunghyun Yoon, Ryan A. Rossi, Handong Zhao, Ruiyi Zhang, Puneet Mathur, Nedim Lipka, Yu Wang, Trung Bui, Franck Dernoncourt, Tianyi Zhou
  [Paper][Code]

• BTS: A Comprehensive Benchmark for Tie Strength Prediction
  [KDD 2025] ACM SIGKDD Conference on Knowledge Discovery & Data Mining
  Xueqi Cheng, Catherine Yang, Yuying Zhao, Yu Wang, Hamid Karimi, Tyler Derr
  [Paper][Code]

• Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective
  [AAAI 2025] AAAI Conference on Artificial Intelligence
  Bo Ni, Yu Wang, Lu Cheng, Erik Blasch, Tyler Derr
  [Paper][Code]

• Edges Matter: Analyzing Graph Time-Series Representations for Temporal Networks
  [TNSE 2025] IEEE Transactions on Network Science and Engineering
  Hongjie Chen, Ryan A. Rossi, Nesreen K. Ahmed, Namyong Park, Yu Wang, Tyler Derr
  [Paper]

• Advancements in Ligand-Based Virtual Screening through the Synergistic Integration of Graph Neural Networks and Expert-Crafted Descriptors
  [JCIM 2025] Journal of Chemical Information and Modeling
  Yunchao Liu, Rocco Moretti, Yu Wang, Ha Dong, Bobby Bodenheimer, Tyler Derr, Jens Meiler

• Augmenting Textual Generation via Topology Aware Retrieval
  [CIKM 2024] ACM International Conference on Information and Knowledge Management
  Yu Wang, Nedim Lipka, Ruiyi Zhang, Alexa Siu, Yuying Zhao, Bo Ni, Xin Wang, Ryan Rossi, Tyler Derr
  [Paper]

• Knowledge Graph-Based Sequential Recommendation with Session-Adaptive Propagation
  [WWW 2024] In Proceedings of the ACM Web Conference
  Yu Wang, Amin Javari, Janani Balaji, Walid Shalaby, Tyler Derr, Xiquan Cui
  [Paper]

• A Topological Perspective on Demystifying GNN-based Link Prediction Performance
  [ICLR 2024] International Conference on Learning Representation
  Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr
  [Paper][Code]

• Knowledge Graph Prompting for Multi-Document Question Answering
  [AAAI 2024] The 38th AAAI Conference on Artificial Intelligence
  Yu Wang, Nedim Lipka, Ryan Rossi, Alexa Siu, Ruiyi Zhang, Tyler Derr
  Best Paper Award (1/70) at GLFrontiers Workshop in Neurips’23
  [Paper][Code]

• WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking
  [NeurIPS 2024] Conference on Neural Information Processing Systems
  Yunchao Liu, Ha Dong, Xin Wang, Rocco Moretti, Yu Wang, Zhaoqian Su, Jiawei Gu, Bobby Bodenheimer, Charles Weaver, Jens Meiler, Tyler Derr
  [Paper][Code]

• Can One Embedding Fit All? A Multi-interest Learning Paradigm Towards Improving User Interest Diversity Fairness
  [WWW 2024] In Proceedings of the ACM Web Conference
  Yuying Zhao, Minghua Xu, Huiyuan Chen, Yuzhong Chen, Yiwei Cai, Rashidul Islam, Yu Wang, Tyler Derr
  [Paper]

• Fair Dating Recommendations for Sexually Fluid Users via Opposite Gender Interaction Ratio
  [AAAI 2024] The 38th AAAI Conference on Artificial Intelligence
  Yuying Zhao, Yu Wang, Yi Zhang, Pamela Wisniswski, Charu Aggarwal, Tyler Derr
  [Paper][Code]

• A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
  [TKDE 2024] IEEE Transactions on Knowledge and Data Engineering
  Yi Zhang, Yuying Zhao, Zhaoqing Li, Xueqi Cheng, Yu Wang, Olivera Kotevska, Philip S. Yu, Tyler Derr
  [Paper]

• Fairness-Aware Graph Neural Networks: A Survey
  [TKDD 2024] ACM Transactions on Knowledge Discovery from Data
  April Chen, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed
  [Paper]

• Collaboration-aware Graph Convolutional Networks for Recommender Systems
  [WWW 2023] In Proceedings of the ACM Web Conference
  Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr
  Top-10 Most Influential Paper in WWW’23
  [Paper][Code]

• Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations
  [AAAI 2023] The 37th AAAI Conference on Artificial Intelligence
  Yuying Zhao, Yu Wang, Tyler Derr
  [Paper][Code][Slides][Poster]

• Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure-Activity Relationship Modeling in Drug Discovery
  [AAAI 2023] The 37th AAAI Conference on Artificial Intelligence
  Yunchao Liu, Yu Wang, Oanh Vu, Rocco Moretti, Bobby Bodenheimer, Jens Meiler, Tyler Derr
  [Paper][Code][Slides][Poster]

• Fairness and Diversity in Recommender Systems: A Survey
  [TIST 2023] ACM Transactions on Intelligent Systems and Technology
  Yuying Zhao, Yu Wang, Yunchao Liu, Xueqi Cheng, Charu Aggarwal, Tyler Derr
  [Paper][Code]

• Imbalanced Graph Classification via GNNs on Graph of Graphs
  [CIKM 2022] In Proceedings of the 31st ACM International Conference on Information and Knowledge Management
  Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr
  Top-10 Most Influential Paper in CIKM’22
  [Paper][Code][Slides][Poster]

• Improving Fairness in GNNs via Mitigating Sensitive Attribute Leakage
  [KDD 2022] Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
  Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr
  [Paper][Code][Slides][Poster]

• Fair Graph Learning with Imbalanced and Biased Data
  [WSDM 2022] ACM International Conference on Web Search and Data Mining
  Yu Wang
  [Paper][Slides]

• On Structural Explanation of Bias in Graph Neural Networks
  [KDD 2022] Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
  Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li
  [Paper][Code]

• ChemicalX: A Deep Learning Library for Drug Pair Scoring
  [KDD 2022] Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Benedek Rozemberczki, Charles Tapley Hoyt, Anna Gogleva, Piotr Grabowski, Klas Karis, Andrej Lamov, Andriy Nikolov, Sebastian Nilsson, Michael Ughetto, Yu Wang, Tyler Derr, Benjamin M Gyori
  [Paper][Code][Slides]

• Tree Decomposed Graph Neural Network
  [CIKM 2021] In Proceedings of the 30th ACM International Conference on Information and Knowledge Management
  Yu Wang, Tyler Derr
  [Paper][Code][Slides][Poster]

• Generating Synthetic Systems of Interdependent Critical Infrastructure Networks
  IEEE Systems Journal 2021
  Yu Wang, Jin-Zhu Yu, Hiba Baroud

• Quantifying the Interdependency Strength Across Critical Infrastructure Systems Using a Dynamic Network Flow Redistribution Model
  [ESRC 2020] Proceedings of the 30th European Safety and Reliability Conference
  Yu Wang, Jinzhu Yu, Hiba Baroud

• A Data-Integration Analysis on Road Emissions and Traffic Patterns
  Smoky Mountains Computational Sciences and Engineering Conference Springer 2020
  Ao Qu, Yu Wang, Yue Hu, Yanbing Wang, Hiba Baroud
  Best Paper Award in 2020 Smoky Mountain Data Challenge Competition by ORNL
  [Paper]

• An Enhanced Percolation Method for Automatic Detection of Cracks in Bridges
  Advances in Civil Engineering 2020
  Qingfei Gao, Yu Wang, Jun Li, Kejian Sheng, Chenguang Liu

Workshop Papers

• Building Trust in Deep Learning-Powered Network Traffic Classification: A Traffic-Explainer Framework
  [SDM-AI4TS 2026] SIAM International Conference on Data Mining, AI for Time Series Workshop
  Riya Ponraj, Ram Durairajan, Yu Wang

• Unveiling Submarine Cable Paths: A Self-Supervised Contrastive Learning Approach
  [IMC-SW 2025] ACM Internet Measurement Conference Student Workshop
  Riya Ponraj, Yu Wang, Ramakrishnan Durairajan

• Mixture of Structural-and-Textual Retrieval over Text-rich Graph
  [NAACL-SRM 2025] Nations of the Americas Chapter of the ACL, Student Research Workshop
  Yongjia Lei, Yu Wang

• Network Management with Graph Machine Learning
  [SECDAI 2024] Security Datasets for AI Workshop
  Yu Wang, Ram Durairajan

• Data-quality Aware Graph Machine Learning
  [SDM-DF 2024] SIAM International Conference on Data Mining Doctoral Forum
  Yu Wang
  Best Poster Award Runner-up

• Knowledge Graph Prompting for Multi-Document Question Answering
  NeurIPS New Frontiers in Graph Learning Workshop (GLFrontiers) 2023 [Paper]
  Yu Wang, Nedim Lipka, Ryan Rossi, Alexa Siu, Ruiyi Zhang, Tyler Derr
  Best Paper Award (1/70)

• Degree-Related Bias in Link Prediction
  [ICDMW 2022] IEEE International Conference on Data Mining Workshops
  Yu Wang, Tyler Derr

• Overcoming Data Quality Issues of Graph Neural Networks
  [SDM-DF 2022] SIAM International Conference on Data Mining Doctoral Forum
  Yu Wang

• Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification
  ACM SIGKDD Workshop on Mining and Learning with Graphs (KDD-MLoG) 2021 [Paper][Code]
  Yu Wang, Charu Aggarwal, Tyler Derr

Preprints

• Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation
  Arxiv 2025
  Zhisheng Qi, Utkarsh Sahu, Li Ma, Haoyu Han, Ryan Rossi, Franck Dernoncourt, Mahantesh Halappanavar, Nesreen Ahmed, Yushun Dong, Yue Zhao, Yu Zhang, Yu Wang
  [Paper][Code]

• Retrieval-augmented Generation with Graphs (GraphRAG)
  Arxiv 2025 [Paper][Code]
  Yu Wang, Haoyu Han, Harry Shomer, Kai Guo, Jiayuan Ding, Yongjia Lei, Mahantesh Halappanavar, Ryan A. Rossi, Subhabrata Mukherjee, Xianfeng Tang, Qi He, Zhigang Hua, Bo Long, Tong Zhao, Neil Shah, Amin Javari, Yinglong Xia, Jiliang Tang

• RAG vs. GraphRAG: A Systematic Evaluation and Key Insights
  Arxiv 2025 [Paper][Code]
  Haoyu Han, Harry Shomer, Yu Wang, Yongjia Lei, Kai Guo, Zhigang Hua, Bo Long, Hui Liu, Jiliang Tang

• Integrating Expert Knowledge with Deep Learning Improves QSAR Models for CADD Modeling
  bioRxiv 2023
  Yunchao Liu, Rocco Moretti, Yu Wang, Bobby Bodenheimer, Tyler Derr, Jens Meiler
  [Paper]

• A Bayesian Approach to Reconstructing Interdependent Infrastructure Networks from Cascading Failures
  Arxiv 2022
  Yu Wang, Jin-Zhu Yu, Hiba Baroud
  [Paper]