Tutorial

• Adversarial Robustness in Graph Neural Networks: Recent Advances and New Frontier

Zhichao Hou, Minhua Lin, Mohamadali Torkamani, Suhang Wang, Xiaorui Liu

IEEE International Conference on Data Science and Advanced Analytics (DSAA 2024)

[tutorial]

• Data Quality-Aware Graph Machine Learning

Yu Wang, Kaize Ding, Xiaorui Liu, Jian Kang, Ryan Rossi, Tyler Derr

International Conference on Information and Knowledge Management (CIKM 2024)

[ website ] [tutorial]

• 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)

[ website ] [slide]

• Large-Scale Graph Neural Networks: Navigating the Past and Pioneering New Horizons

Rui Xue, Haoyu Han, Tong Zhao, Neil Shah, Jiliang Tang, Xiaorui Liu

SIAM International Conference on Data Mining (SDM 2024)

[ website ] [slide]

• Large-Scale Graph Neural Networks: Navigating the Past and Pioneering New Horizons

Rui Xue, Haoyu Han, Tong Zhao, Neil Shah, Jiliang Tang, Xiaorui Liu

Association for the Advancement of Artificial Intelligence (AAAI 2024)

[ website ] [ slide ]

• Large-Scale Graph Neural Networks: The Past and New Frontiers

Rui Xue, Haoyu Han, Tong Zhao, Neil Shah, Jiliang Tang, Xiaorui Liu

International Conference on Knowledge Discovery & Data Mining (KDD 2023)

[ website ] [ slide ]

• Trustworthy AI: A Computational Perspective

Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lyu, Jiliang Tang.
International World Wide Web Conference (WWW 2022)
[ website ] [ slide ] [video]

• Communication Efficient Distributed Learning
  Xiaorui Liu, Yao Li, Ming Yan, Jiliang Tang.
  International Joint Conference on Artificial Intelligence (IJCAI 2021)
  [ website ] [slide]

• Adversarial Robustness in Deep Learning: From Practices to Theories
  Han Xu, Yaxin Li, Xiaorui Liu, Wentao Wang, Jiliang Tang
  International Conference on Knowledge Discovery & Data Mining (KDD 2021)
  [website] [slide]

• Graph Representation Learning: Foundations, Methods, Applications, and Systems
  Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang
  International Conference on Knowledge Discovery & Data Mining (KDD 2021)
  [website] [slide]

• Trustworthy AI: A Computational Perspective
  Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Yaxin Li, Jiliang Tang.
  International Conference on Automated Planning and Scheduling (ICAPS 2021)
  [ website ] [ slide ]

Publication 

[* indicates equal contribution]    Google Scholar 

• Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization

Weizhi Gao, Zhichao Hou, Junqi Yin, Feiyi Wang, Linyu Peng, Xiaorui Liu

International Conference on Machine Learning (ICML 2025)

• Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks

Rui Xue, Tong Zhao, Neil Shah, Xiaorui Liu

International Conference on Machine Learning (ICML 2025)

• Efficient End-to-end Language Model Fine-tuning on Graphs

Rui Xue, Xipeng Shen, Ruozhou Yu, Xiaorui Liu

ACM International Conference on Knowledge Discovery & Data Mining (KDD 2025)

• Robustness Reprogramming for Representation Learning

Zhichao Hou, MohamadAli Torkamani, Hamid Krim, Xiaorui Liu

International Conference on Learning Representations (ICLR 2025)
Spotlight paper (1.4% ≈ 162/11670)

• Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing

Weizhi Gao, Zhichao Hou, Han Xu, Xiaorui Liu

Conference on Neural Information Processing Systems (NeurIPS 2024)

• ProTransformer: Robustify Transformers via Plug-and-Play Paradigm

Zhichao Hou, Weizhi Gao, Yuchen Shen, Feiyi Wang, Xiaorui Liu

Conference on Neural Information Processing Systems (NeurIPS 2024)

• Robust Graph Neural Networks via Unbiased Aggregation

Zhichao Hou, Ruiqi Feng, Tyler Derr, Xiaorui Liu

Conference on Neural Information Processing Systems (NeurIPS 2024)

• A Brief Review of Hemp Fiber Length Measurement Techniques

Joia Green, Xiaorui Liu, Rong Yin

Fibers, 2024

• Automated Polynomial Filter Learning for Graph Neural Networks

Wendi Yu, Zhichao Hou, Xiaorui Liu

IEEE International Conference on Big Data (BigData 2024)

• Manufacturing Service Capability Prediction with Graph Neural Networks

Yunqing Li, Xiaorui Liu, Binil Starly

Journal of Manufacturing Systems, 2024

• ProTransformer: Robustify Transformers via Plug-and-Play Paradigm

Zhichao Hou, Weizhi Gao, Yuchen Shen, Xiaorui Liu

ICLR 2024 Workshop on Reliable and Responsible Foundation Models (ICLR 2024 R2-FM)

• Efficient Large Language Models Fine-Tuning on Graphs

Rui Xue, Xipeng Shen, Ruozhou Yu, Xiaorui Liu

The Web Conference Workshop on Large Language Models (LLMs) for Graph Learning (WWW 2024 LLMs4Graph)

• Linear-Time Graph Neural Networks for Scalable Recommendations

Jiahao Zhang*, Rui Xue*, Wenqi Fan, Xu Xin, Qing Li, Jian Pei, Xiaorui Liu

International World Wide Web Conference (The Web Conference) (WWW 2024)

• Structural Fairness-aware Active Learning for Graph Neural Networks 

Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada

International Conference on Learning Representations (ICLR 2024)

• Towards Label Position Bias in Graph Neural Networks 

Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang

Conference on Neural Information Processing Systems (NeurIPS 2023)

• How Does the Memorization of Neural Networks Impact Adversarial Robust Models?
  Han Xu, Xiaorui Liu, Wentao Wang, Zitao Liu, Anil Jain, Jiliang Tang

ACM International Conference on Knowledge Discovery & Data Mining (KDD 2023)

• Enhancing Graph Representations Learning with Decorrelated Propagation

Hua Liu, Haoyu Han, Wei Jin, Xiaorui Liu, Hui Liu

ACM International Conference on Knowledge Discovery & Data Mining (KDD 2023)

• LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation

Rui Xue, Haoyu Han, Ali Torkamani, Jian Pei, Xiaorui Liu

International Conference on Machine Learning (ICML 2023)

• Alternately Optimized Graph Neural Networks

Haoyu Han, Xiaorui Liu, Haitao Mao, Ali Torkamani, Feng Shi, Victor Lee, Jiliang Tang

International Conference on Machine Learning (ICML 2023)

• Federated IoT Interaction Vulnerability Analysis
  Guangjing Wang, Hanqing Guo, Anran Li, Xiaorui Liu, Qiben Yan

IEEE International Conference on Data Engineering (ICDE 2023)

• Jointly Attacking Graph Neural Network and its Explanations
  Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, et al.

IEEE International Conference on Data Engineering (ICDE 2023)

• Trustworthy AI: A Computational Perspective
  Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, et al.
  ACM Transactions on Intelligent Systems and Technology (TIST 2022)

• Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
  Wei Jin, Xiaorui Liu, Yao Ma, Charu Aggarwal, Jiliang Tang.
  ACM International Conference on Knowledge Discovery & Data Mining (KDD 2022)

• Graph Trend Filtering Networks for Recommendations
  Wenqi Fan*, Xiaorui Liu*, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li.
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022)

• Automated Self-Supervised Learning for Graphs
  Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang.
  International Conference on Learning Representations (ICLR 2022)

• Is Homophily a Necessity for Graph Neural Networks?
  Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang.
  International Conference on Learning Representations (ICLR 2022)

• Imbalanced Adversarial Training with Reweighting
  Wentao Wang, Han Xu, Xiaorui Liu, Yaxin Li, Bhavani Thuraisingham, Jiliang Tang.
  Proceedings of the IEEE International Conference on Data Mining (ICDM 2022).

• Learning from Imbalanced Crowdsourced Labeled Data
  Wentao Wang, Joseph Thekinen, Xiaorui Liu, Zitao Liu, Jiliang Tang.
  SIAM International Conference on Data Mining (SDM 2022).

• Graph Neural Networks with Adaptive Residual
  Xiaorui Liu, Jiayuan Jin, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang.
  Conference on Neural Information Processing Systems (NeurIPS 2021)
  [ paper ] [ appendix ] [ slide ] [ poster ] [ code ] [ bibtex ]

• Graph Feature Gating Network
  Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu Aggarwal, Jiliang Tang.
  The Conference on Information and Knowledge Management (CIKM 2021)
  [ paper ] [ bibtex ]

• A Unified View on Graph Neural Networks as Graph Signal Denoising
  Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah.
  The Conference on Information and Knowledge Management (CIKM 2021)
  [ paper ] [ bibtex ]

• Deep Adversarial Network Alignment
  Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu, Jiliang Tang.
  The Conference on Information and Knowledge Management (CIKM 2021)
  [ paper ] [ bibtex ]

• Elastic Graph Neural Networks
  Xiaorui Liu*, Wei Jin*, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang.
  International Conference on Machine Learning (ICML 2021)
  Oral paper (3% ≈ 166/5513)
  [ paper ] [ video ] [ slide ] [ poster ] [ code ] [ bibtex ]

• To be Robust or to be Fair: Towards Fairness in Adversarial Training
  Xiaorui Liu*, Han Xu*, Yaxin Li, Anil Jain, Jiliang Tang.
  International Conference on Machine Learning (ICML 2021)
  Spotlight paper (21% ≈ 1184/5513)
  [ paper ] [ video ] [ slide ] [ bibtex ]

• Linear Convergent Decentralized Optimization with Compression
  Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang, Ming Yan.
  International Conference on Learning Representations (ICLR 2021)
  Score ranking (3% ≈ 77/2976)
  [ paper ] [ slide ] [ poster ] [ video ] [ bibtex ]

• Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
  Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang.
  SIAM International Conference on Data Mining (SDM 2021)
  [ paper ] [ bibtex ]

• A Double Residual Compression Algorithm for Efficient Distributed Learning
  Xiaorui Liu, Yao Li, Jiliang Tang and Ming Yan.
  International Conference on Artificial Intelligence and Statistics (AISTATS 2020)
  [ abs ] [ paper ] [ supplementary ] [ slide ] [ video ] [ bibtex ]

• Graph Structure Learning for Robust Graph Neural Networks
  Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang.
  ACM International Conference on Knowledge Discovery & Data Mining (KDD 2020)
  [ paper ] [ code ] [ slide ] [ bibtex ]

• Deep Adversarial Canonical Correlation Analysis
  Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li, and Jiliang Tang.
  SIAM International Conferenceon Data Mining (SDM 2020)
  [ paper ] [ bibtex ]

• Epidemic Graph Convolutional Network
  Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu Aggarwal and Jiliang Tang.
  ACM International Conference on Web Search and Data Mining (WSDM 2020)
  [ paper ] [ code ] [ bibtex ]

• Weight Loss Prediction in Social-Temporal Context
  Zhiwei Wang, Xiaorui Liu, Jiliang Tang and Dawei Yin.
  IEEE International Conference on Healthcare Informatics (ICHI 2019)
  [ paper ] [ bibtex ]
  Best Paper Honorable Mention Award

• A Survey on Dialogue Systems: Recent Advances and New Frontiers
  Hongshen Chen, Xiaorui Liu, Dawei Yin and Jiliang Tang.
  ACM SIGKDD Explorations Newsletter (SIGKDD Explorations 2017).
  [ paper ] [ bibtex ]

• Fingertip in the Eye: An Attention-Based Method for Real-Time Hand Tracking and Fingertip Detection in Egocentric Videos
  Xiaorui Liu, Yichao Huang, Xin Zhang and Lianwen Jin.
  Chinese Conference on Pattern Recognition (CCPR 2016).

• A Pointing Gesture based Egocentric Interaction System: Dataset, Approach and Application
  Yichao Huang, Xiaorui Liu, Xin Zhang and Lianwen Jin.
  CVPR Workshop 2016. Check out our demo for Real-time Air Writing System!

• Deepfinger: A Cascade Convolutional Neural Network Approach to Finger Key Point Detection in Egocentric Vision with Mobile Camera
  Yichao Huang, Xiaorui Liu, Lianwen Jin and Xin Zhang.
  IEEE International Conference on Systems, Man, and Cybernetics (SMC 2015).

Preprint (arXiv)

• Traffic Engineering in Large-scale Networks with Generalizable Graph Neural Networks

Fangtong Zhou, Xiaorui Liu, Ruozhou Yu, Guoliang Xue

• Boosting Adversarial Robustness and Generalization with Structural Prior

Zhichao Hou, Weizhi Gao, Hamid Krim, Xiaorui Liu

• Exploring Potentials and Challenges of Using LLMs for the Transcriptional Regulation Analysis of Long Non-coding RNAs

Wei Wang, Zhichao Hou, Xiaorui Liu, Xinxia Peng

• Graph Machine Learning in the Era of Large Language Models (LLMs)

Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Xiaorui Liu, et al

• Rethinking Large Language Model Architectures for Sequential Recommendations

Hanbing Wang, Xiaorui Liu, et al

• Can Directed Graph Neural Networks be Adversarially Robust?

Zhichao Hou, Xitong Zhang, Wei Wang, Charu Aggarwal, Xiaorui Liu

• Towards Fair Classification against Poisoning Attacks

Han Xu, Xiaorui Liu, Yuxuan Wan, Jiliang Tang

• Defense Against Gradient Leakage Attacks via Learning to Obscure Data

     Yuxuan Wan, Han Xu, Xiaorui Liu, Jie Ren, Wenqi Fan, Jiliang Tang

• Enhancing Adversarial Training with Feature Separability

     Yaxin Li, Xiaorui Liu, Han Xu, Wentao Wang, Jiliang Tang

• Decentralized Composite Optimization with Compression
  Xiaorui Liu*, Yao Li*, Jiliang Tang, Ming Yan, Kun Yuan.