You may also see our work on Google Scholar.
Retrieval-Augmented Generation with Graphs (GraphRAG)
Haoyu Han, Yu Wang, 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.
https://arxiv.org/abs/2501.00309v1 (2025).
Personalized Graph-Based Retrieval for Large Language Models
Steven Au, Cameron J. Dimacali, Ojasmitha Pedirappagari, Namyong Park, Franck Dernoncourt, Yu Wang, Nikos Kanakaris, Hanieh Deilamsalehy, Ryan A. Rossi, Nesreen K. Ahmed.
https://arxiv.org/abs/2501.02157 (2025).
GUI Agents: A Survey
Dang Nguyen, Jian Chen, Yu Wang, Gang Wu, Namyong Park, Zhengmian Hu, Hanjia Lyu, Junda Wu, Ryan Aponte, Yu Xia, Xintong Li, Jing Shi, Hongjie Chen, Viet Dac Lai, Zhouhang Xie, Sungchul Kim, Ruiyi Zhang, Tong Yu, Mehrab Tanjim, Nesreen K. Ahmed, Puneet Mathur, Seunghyun Yoon, Lina Yao, Branislav Kveton, Thien Huu Nguyen, Trung Bui, Tianyi Zhou, Ryan A. Rossi, Franck Dernoncourt.
https://arxiv.org/abs/2412.13501 (2024).
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.
https://arxiv.org/abs/2411.01747 (2024). code
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.
https://arxiv.org/abs/2411.00027 (2024).
A survey of small language models
Chien Van Nguyen, Xuan Shen, Ryan Aponte, Yu Xia, Samyadeep Basu, Zhengmian Hu, Jian Chen, Mihir Parmar, Sasidhar Kunapuli, Joe Barrow, Junda Wu, Ashish Singh, Yu Wang, Jiuxiang Gu, Franck Dernoncourt, Nesreen K. Ahmed, Nedim Lipka, Ruiyi Zhang, Xiang Chen, Tong Yu, Sungchul Kim, Hanieh Deilamsalehy, Namyong Park, Mike Rimer, Zhehao Zhang, Huanrui Yang, Ryan A. Rossi, Thien Huu Nguyen.
https://arxiv.org/abs/2410.20011 (2024).
Advancements in Ligand-Based Virtual Screening through the Synergistic Integration of Graph Neural Networks and Expert-Crafted Descriptors
Yunchao “Lance” Liu, Rocco Moretti, Yu Wang, Bobby Bodenheimer, Tyler Derr, Jens Meiler.
bioRxiv preprint (2024).
Large Generative Graph Models
Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr.
https://arxiv.org/abs/2406.05109 (2024).
Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective
Bo Ni, Yu Wang, Lu Cheng, Erik Blasch, Tyler Derr.
In Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI), Philadelphia, PA, February 25-March 4, 2025.
WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking
Ha Dong, Xin Wang, Rocco Moretti, Yu Wang, Zhaoqian Su, Jiawei Gu, Bobby Bodenheimer, Charles David Weaver, Jens Meiler, Tyler Derr.
Advances in Neural Information Processing (NeurIPS), Vancouver, Canada, December 10 - 15, 2024.
Topology-aware Retrieval Augmentation for Text Generation
Yu Wang, Nedim Lipka, Ruiyi Zhang, Alexa Siu, Yuying Zhao, Bo Ni, Xin Wang, Ryan Rossi, Tyler Derr.
In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, ID, October 21-25, 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.
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.
Knowledge Graph-based Session Recommendation with Session-Adaptive Propagation
Yu Wang, Amin Javari, Janani Balaji, Walid Shalaby, Tyler Derr, Xiquan Cui.
Proceedings of the ACM Web Conference (WWW), Singapore, May 13-17, 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.
Proceedings of the ACM Web Conference (WWW), Singapore, May 13-17, 2024.
Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation
Yuying Zhao, Yu Wang, Yi Zhang, Pamela Wisniewski, Charu Aggarwal, Tyler Derr.
In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, February 20-27, 2024.
Knowledge Graph Prompting for Multi-Document Question Answering
Yu Wang, Nedim Lipka, Ryan A. Rossi, Alexa Siu, Ruiyi Zhang, Tyler Derr.
In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, February 20-27, 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.
The Twelfth International Conference on Learning Representations (ICLR), Vienna, Austria, May 7-11, 2024.
Fair Online Dating Recommendations for Sexually Fluid Users via Leveraging Opposite Gender Interaction Ratio
Yuying Zhao, Yu Wang, Yi Zhang, Pamela Wisniewski, Charu Aggarwal, Tyler Derr.
non-archival version accepted at Mining and Learning on Graphs (MLG) Workshop at KDD 2023.
A Bayesian Approach for Inferring the Topology of Interdependent Infrastructure Networks
Yu Wang, Jinzhu Yu, Hiba Baroud.
In Proceedings of the ACM Web Conference 2023 (TheWebConf), Austin, TX, USA, April 30 - May 4, 2023.
Collaboration-Aware Graph Convolutional Network for Recommender Systems
Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr.
14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 14, Dublin, Ireland, July 9-13, 2023.
Fairness and Explainability: Briding the Gap Towards Fair Model Explanations
Yuying Zhao, Yu Wang, Tyler Derr.
In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, February 7-14, 2023.
Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Relationship Modeling in Drug Discovery
Yunchao “Lance” Liu, Yu Wang, Oanh Vu, Rocco Moretti, Bobby Bodenheimer, Jens Meiler, Tyler Derr.
In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, February 7-14, 2023.
Degree-related Bias in Link Prediction
Yu Wang and Tyler Derr.
In Proceedings of the 22nd International Conference on Data Mining Workshop (ICDMW) Machine Learning on Graphs (MLoG), Orlando, FL, USA, November 28 - December 1, 2022.
Imbalanced Graph Classification via Graph-of-Graph Neural Networks
Yu Wang, Yuying Zhao, Neil Shah, and Tyler Derr.
In Proceedings of the 31th ACM International Conference on Information and Knowledge Management (CIKM), Atlanta, GA, USA, October 17-21, 2022.
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute
Leakage
Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, and Tyler Derr.
In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington D.C., USA, August 14-18, 2022
On Structural Explanation of Bias in Graph Neural Networks
Yushun Dong, Song Wang, Yu Wang, Tyler Derr, and Jundong Li.
In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington D.C., USA, August 14-18, 2022
ChemicalX: A Deep Learning Library for Drug Pair Scoring
Benedek Rozemberczki, Charles Hoyt, Anna Gogleva, Piotr Grabowski, Klas Karis, Andrej Lamov, Andriy Nikolov, Sebastian Nilsson, Michael Ughetto, Yu Wang, Tyler Derr, and Benjamin Gyori.
In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington D.C., USA, August 14-18, 2022
Fair Graph Representation Learning with Imbalanced and Biased Data
Yu Wang.
Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM), Virtual Conf., February 21-25, 2022
Graph Neural Networks: Self-supervised Learning
Yu Wang, Wei Jin, and Tyler Derr
Graph Neural Networks: Foundations, Frontiers, and Applications (Lingfei Wu, Peng Cui, Jian Pei, and Liang Zhao (Eds.)), Springer, Chapter 18. 2022
Comparing Topology-based and Flow-based Resilience Assessment of Interdependent Infrastructure Networks
Jinzhu Yu, Yu Wang, and Hiba Baroud
13th International Conference on Structural Safety and Reliability, ICOSSAR 2021-2022, Tongji University, Shanghai, China
Tree Decomposed Graph Neural Network
Yu Wang and Tyler Derr
In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM), Virtual Conf., November 1-5, 2021
Generating Synthetic Systems of Interdependent Critical Infrastructure Systems
Yu Wang, Jin-Zhu Yu, and Hiba Baroud
IEEE Systems Journal, 2021
Quantifying the Interdependency Strength Across Critical Infrastructure Systems Using A Dynamic Network Flow Redistribution Model.
Yu Wang, Jin-Zhu Yu, and Hiba Baroud
Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference
A data-integration analysis on road emissions and traffic patterns.
Ao Qu, Yu Wang, Yue Hu, Yanbing Wang, and Hiba Baroud
17th Smoky Mountains Computational Sciences and Engineering Conference, 2020
An enhanced percolation method for automatic detection of cracks in concrete bridges
Qingfei Gao, Yu Wang, Jun Li, Kejian Sheng, Chenguang Liu
Advances in Civil Engineering, 2020