You may also see our work on Google Scholar.
Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation
Zhisheng Qi, Utkarsh Sahu, Li Ma, Haoyu Han, Ryan Rossi, Franck Dernoncourt, Mahantesh Halappanavar, Nesreen Ahmed, Yushun Dong, Yue Zhao, Yu Zhang, Yu Wang.
arXiv, 2025.
Retrieval-augmented Generation with Graphs (GraphRAG)
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.
arXiv, 2025.
RAG vs. GraphRAG: A Systematic Evaluation and Key Insights
Haoyu Han, Harry Shomer, Yu Wang, Yongjia Lei, Kai Guo, Zhigang Hua, Bo Long, Hui Liu, Jiliang Tang.
arXiv, 2025.
Integrating Expert Knowledge with Deep Learning Improves QSAR Models for CADD Modeling
Yunchao Liu, Rocco Moretti, Yu Wang, Bobby Bodenheimer, Tyler Derr, Jens Meiler.
bioRxiv, 2023.
A Bayesian Approach to Reconstructing Interdependent Infrastructure Networks from Cascading Failures
Yu Wang, Jin-Zhu Yu, Hiba Baroud.
arXiv, 2022.
SURGeLLM: Structured Understanding, Retrieval, and Generation in LLMs era
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.
Annual Meeting of the Association for Computational Linguistics (ACL), 2026. [Website]
Machine Learning on Graphs in the Era of Generative Artificial Intelligence
Yu Wang, Yu Zhang, Zhichun Guo, Harry Shomer, Haoyu Han, Tyler Derr, Nesreen Ahmed, Mahantesh Halappanavar, Jiliang Tang.
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2025. [Website]
Rigorizing Retrieval-augmented Generation with Structural Intelligence
Zhisheng Qi, Yongjia Lei, Haoyu Han, Harry Shomer, Kaize Ding, Yu Zhang, Ryan Rossi, Hui Liu, Yu Wang.
ACM International Conference on Web Search and Data Mining (WSDM), 2026. [Website]
Empowering Retrieval-augmented Generation with Graph-structured Knowledge
Yu Wang, Haoyu Han, Harry Shomer, Kai Guo, Yongjia Lei, Jiayuan Ding, Xianfeng Tang, Qi He, Jiliang Tang.
SIAM International Conference on Data Mining (SDM), 2025. [Website]
Data Quality-Aware Graph Machine Learning
Yu Wang, Kaize Ding, Xiaorui Liu, Jian Kang, Ryan Rossi, Tyler Derr.
ACM International Conference on Information and Knowledge Management (CIKM), 2024. [Website]
Data Quality-aware Graph Machine Learning
Yu Wang, Yijun Tian, Tong Zhao, Xiaorui Liu, Jian Kang, Tyler Derr.
SIAM International Conference on Data Mining (SDM), 2024.
Graph Neural Networks: Self-supervised Learning
Yu Wang, Wei Jin, Tyler Derr.
In Graph Neural Networks: Foundations, Frontiers, and Applications (Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Eds.), Springer Nature, 2022. [Book]
Building Transparency in Deep Learning-Powered Network Traffic Classification: A Traffic-Explainer Framework
Riya Ponraj, Ram Durairajan, Yu Wang.
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2026.
SaVe-TAG: Semantic-aware Vicinal Risk Minimization for Long-Tailed Text-Attributed Graphs
Leyao Wang, Yu Wang, Bo Ni, Yuying Zhao, Haoyu Wang, Yao Ma, Tyler Derr.
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2026.
Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs
Haoyu Han, Kai Guo, Harry Shomer, Yu Wang, Yucheng Chu, Hang Li, Li Ma, Jiliang Tang.
The ACM Web Conference (WWW), 2026.
A Survey on LLM-based Conversational User Simulation
Bo Ni, Leyao Wang, Yu Wang, Yuying Zhao, Tyler Derr, Ryan A. Rossi.
Conference of European Chapter of Association for Computational Linguistics (EACL), 2026.
Rule Mining and Learning for Structured Knowledge Retrieval
Yongjia Lei, Mahantesh M Halappanavar, Yu Wang.
ACM International Conference on Web Search and Data Mining (WSDM), 2026.
Knowledge Homophily in Large Language Models
Utkarsh Sahu, Zhisheng Qi, Mahantesh M Halappanavar, Nedim Lipka, Ryan A Rossi, Franck Dernoncourt, Yu Zhang, Yao Ma, Yu Wang.
ACM International Conference on Web Search and Data Mining (WSDM), 2026.
Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases
Yongjia Lei, Haoyu Han, Ryan A Rossi, Franck Dernoncourt, Nedim Lipka, Mahantesh M Halappanavar, Jiliang Tang, Yu Wang.
Annual Meeting of the Association for Computational Linguistics (ACL Findings), 2025.
Best Poster Honorable Mention at SDM’25 Doctoral Forum
From Selection to Generation: A Survey of LLM-based Active Learning
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.
Annual Meeting of the Association for Computational Linguistics (ACL), 2025.
Personalization of Large Language Models: A Survey
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.
Transactions on Machine Learning Research (TMLR), 2025.
Demystifying the Power of LLMs in Graph Generation
Yu Wang, Ryan A Rossi, Namyong Park, Nesreen K Ahmed, Danai Koutra, Franck Dernoncourt, Tyler Derr.
Nations of Americas Chapter of Association for Computational Linguistics (NAACL Findings), 2025.
Large Graph Generative Models
Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr.
International Conference on Learning Representations (ICLR), 2025.
Edge Classification: New Directions in Topological Imbalance
Yu Wang, Xueqi Cheng, Yuying Zhao, Charu Aggarwal, Tyler Derr.
ACM International Conference on Web Search and Data Mining (WSDM), 2025.
Empowering GraphRAG with Knowledge Filtering and Integration
Kai Guo, Harry Shomer, Shenglai Zeng, Haoyu Han, Yu Wang, Jiliang Tang.
Empirical Methods in Natural Language Processing (EMNLP), 2025.
DynaSaur: Large Language Agents Beyond Predefined Actions
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.
Second Conference on Language Modeling (COLM), 2025.
BTS: A Comprehensive Benchmark for Tie Strength Prediction
Xueqi Cheng, Catherine Yang, Yuying Zhao, Yu Wang, Hamid Karimi, Tyler Derr.
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2025.
Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective
Bo Ni, Yu Wang, Lu Cheng, Erik Blasch, Tyler Derr.
AAAI Conference on Artificial Intelligence (AAAI), 2025.
Edges Matter: Analyzing Graph Time-Series Representations for Temporal Networks
Hongjie Chen, Ryan A. Rossi, Nesreen K. Ahmed, Namyong Park, Yu Wang, Tyler Derr.
IEEE Transactions on Network Science and Engineering (TNSE), 2025.
Advancements in Ligand-Based Virtual Screening through the Synergistic Integration of Graph Neural Networks and Expert-Crafted Descriptors
Yunchao Liu, Rocco Moretti, Yu Wang, Ha Dong, Bobby Bodenheimer, Tyler Derr, Jens Meiler.
Journal of Chemical Information and Modeling (JCIM), 2025.
Augmenting Textual Generation via Topology Aware Retrieval
Yu Wang, Nedim Lipka, Ruiyi Zhang, Alexa Siu, Yuying Zhao, Bo Ni, Xin Wang, Ryan Rossi, Tyler Derr.
ACM International Conference on Information and Knowledge Management (CIKM), 2024.
WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking
Yunchao Liu, Ha Dong, Xin Wang, Rocco Moretti, Yu Wang, Zhaoqian Su, Jiawei Gu, Bobby Bodenheimer, Charles Weaver, Jens Meiler, Tyler Derr.
Conference on Neural Information Processing Systems (NeurIPS), 2024.
Knowledge Graph-Based Sequential Recommendation with Session-Adaptive Propagation
Yu Wang, Amin Javari, Janani Balaji, Walid Shalaby, Tyler Derr, Xiquan Cui.
The ACM Web Conference (WWW), 2024.
Can One Embedding Fit All? A Multi-interest Learning Paradigm Towards Improving User Interest Diversity Fairness
Yuying Zhao, Minghua Xu, Huiyuan Chen, Yuzhong Chen, Yiwei Cai, Rashidul Islam, Yu Wang, Tyler Derr.
The ACM Web Conference (WWW), 2024.
A Topological Perspective on Demystifying GNN-based Link Prediction Performance
Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr.
International Conference on Learning Representations (ICLR), 2024.
Knowledge Graph Prompting for Multi-Document Question Answering
Yu Wang, Nedim Lipka, Ryan A. Rossi, Alexa Siu, Ruiyi Zhang, Tyler Derr.
AAAI Conference on Artificial Intelligence (AAAI), 2024.
Best Paper Award (1/70) at GLFrontiers Workshop in NeurIPS’23
Fair Dating Recommendations for Sexually Fluid Users via Opposite Gender Interaction Ratio
Yuying Zhao, Yu Wang, Yi Zhang, Pamela Wisniswski, Charu Aggarwal, Tyler Derr.
AAAI Conference on Artificial Intelligence (AAAI), 2024.
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
Yi Zhang, Yuying Zhao, Zhaoqing Li, Xueqi Cheng, Yu Wang, Olivera Kotevska, Philip S. Yu, Tyler Derr.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
Fairness-Aware Graph Neural Networks: A Survey
April Chen, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed.
ACM Transactions on Knowledge Discovery from Data (TKDD), 2024.
Collaboration-aware Graph Convolutional Networks for Recommender Systems
Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr.
The ACM Web Conference (WWW), 2023.
Top-10 Most Influential Paper in WWW’23
Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations
Yuying Zhao, Yu Wang, Tyler Derr.
AAAI Conference on Artificial Intelligence (AAAI), 2023.
Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure-Activity Relationship Modeling in Drug Discovery
Yunchao Liu, Yu Wang, Oanh Vu, Rocco Moretti, Bobby Bodenheimer, Jens Meiler, Tyler Derr.
AAAI Conference on Artificial Intelligence (AAAI), 2023.
Fairness and Diversity in Recommender Systems: A Survey
Yuying Zhao, Yu Wang, Yunchao Liu, Xueqi Cheng, Charu Aggarwal, Tyler Derr.
ACM Transactions on Intelligent Systems and Technology (TIST), 2023.
Imbalanced Graph Classification via GNNs on Graph of Graphs
Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr.
ACM International Conference on Information and Knowledge Management (CIKM), 2022.
Top-10 Most Influential Paper in CIKM’22
Improving Fairness in GNNs via Mitigating Sensitive Attribute Leakage
Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr.
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2022.
On Structural Explanation of Bias in Graph Neural Networks
Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li.
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2022.
ChemicalX: A Deep Learning Library for Drug Pair Scoring
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.
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2022.
Fair Graph Representation Learning with Imbalanced and Biased Data
Yu Wang.
ACM International Conference on Web Search and Data Mining (WSDM), 2022.
Tree Decomposed Graph Neural Network
Yu Wang, Tyler Derr.
ACM International Conference on Information and Knowledge Management (CIKM), 2021.
Generating Synthetic Systems of Interdependent Critical Infrastructure Networks
Yu Wang, Jin-Zhu Yu, Hiba Baroud.
IEEE Systems Journal, 2021.
A Data-Integration Analysis on Road Emissions and Traffic Patterns
Ao Qu, Yu Wang, Yue Hu, Yanbing Wang, Hiba Baroud.
Smoky Mountains Computational Sciences and Engineering Conference, 2020.
Best Paper Award in 2020 Smoky Mountain Data Challenge Competition by ORNL
Quantifying the Interdependency Strength Across Critical Infrastructure Systems Using a Dynamic Network Flow Redistribution Model
Yu Wang, Jin-Zhu Yu, Hiba Baroud.
European Safety and Reliability Conference (ESRC), 2020.
An Enhanced Percolation Method for Automatic Detection of Cracks in Bridges
Qingfei Gao, Yu Wang, Jun Li, Kejian Sheng, Chenguang Liu.
Advances in Civil Engineering, 2020.
Building Trust in Deep Learning-Powered Network Traffic Classification: A Traffic-Explainer Framework
Riya Ponraj, Ram Durairajan, Yu Wang.
SIAM International Conference on Data Mining, AI for Time Series Workshop (SDM-AI4TS), 2026.
Unveiling Submarine Cable Paths: A Self-Supervised Contrastive Learning Approach
Riya Ponraj, Yu Wang, Ramakrishnan Durairajan.
ACM Internet Measurement Conference Student Workshop (IMC-SW), 2025.
Mixture of Structural-and-Textual Retrieval over Text-rich Graph
Yongjia Lei, Yu Wang.
Nations of the Americas Chapter of the ACL, Student Research Workshop (NAACL-SRM), 2025.
Network Management with Graph Machine Learning
Yu Wang, Ram Durairajan.
Security Datasets for AI Workshop (SECDAI), 2024.
Data-quality Aware Graph Machine Learning
Yu Wang.
SIAM International Conference on Data Mining Doctoral Forum (SDM-DF), 2024.
Best Poster Award Runner-up
Knowledge Graph Prompting for Multi-Document Question Answering
Yu Wang, Nedim Lipka, Ryan Rossi, Alexa Siu, Ruiyi Zhang, Tyler Derr.
NeurIPS New Frontiers in Graph Learning Workshop (GLFrontiers), 2023.
Best Paper Award (1/70)
Degree-Related Bias in Link Prediction
Yu Wang, Tyler Derr.
IEEE International Conference on Data Mining Workshops (ICDMW), 2022.
Overcoming Data Quality Issues of Graph Neural Networks
Yu Wang.
SIAM International Conference on Data Mining Doctoral Forum (SDM-DF), 2022.
Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification
Yu Wang, Charu Aggarwal, Tyler Derr.
ACM SIGKDD Workshop on Mining and Learning with Graphs (KDD-MLoG), 2021.