Lihui Liu

I am an assistant professor at Wayne State University. My research interests lie in neural symbolic AI, large language models, augmented retrieval, knowledge graph reasoning, and graph neural networks.

I got my Ph.D. in the Department of Computer Science at University of Illinois at Urbana-Champaign in 2024. Before that, I obtained my M.S degree from Chinese Academy of Sciences, Institute of Software (2014-2017) and B.S degree from HuaZhong University of Science and Technology (2010-2014).

I have several Ph.D. positions available and am always looking for self-motivated Ph.D. students to join my team. If you are interested in my research, please feel free to reach out to me via email with the subject line ‘Ph.D. Application – [Your Name].’. (hw6926 at wayne dot edu)

Google Scholar

Conferences

18. Prompt tuning with attribute guidance for entity matching. 2024 under review
Lihui Liu, Jinha Kim, Vidit Bansal

17. Logic Query of Thoughts: Guiding Large Language Models to Answer Complex Logic Queries with Knowledge Graphs. 2024 arxiv
Lihui Liu, Zihao Wang, Ruizhong Qiu, Yikun Ban, Eunice Chan, Jingrui He, Hanghang Tong

16. Conversational Question Answering with Reformulations over Knowledge Graph. ACL 2024 Findings [paper](https://arxiv.org/abs/2312.17269)
Lihui Liu, Blaine Hill, Boxin Du, Hanghang Tong

15. Can contrastive learning refine embedding. 2024 ESWC
Lihui Liu, Jimha Kim, Vidit Bansal.

14. Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform. 2024 WSDM 
Blaine Hill, Lihui Liu, Hanghang Tong

13. PaCEr: Positional Embedding Meets Structural Embedding of Graph Representation Learning. 2024 WWW
Yuchen Yan, Yongyi Hu, Qinghai Zhou, Lihui Liu, Hanghang Tong

12. Reconciling Competing Sampling Strategies of Network Embedding. NeurIPS 2023 [paper](https://proceedings.neurips.cc/paper_files/paper/2023/file/15dc2344ea9bdc01ffb8bb2d692e4018-Paper-Conference.pdf)
Yuchen Yan, Baoyu Jing, Lihui Liu, Ruijie Wang, Jinning Li, Tarek Abdelzaher, Hanghang Tong

11. Knowledge Graph Question Answering with Ambiguous Query. WWW 2023 [paper](https://dl.acm.org/doi/abs/10.1145/3543507.3583316)
Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong	

10. Comparative Reasoning for Knowledge Graph Fact Checking. BigData 2022 [paper](https://ieeexplore.ieee.org/document/10020991)
Lihui Liu, Houxiang Ji, Jiejun Xu, Hanghang Tong

9. Joint Knowledge Graph Completion and Question Answering. KDD 2022 [paper](https://dl.acm.org/doi/abs/10.1145/3534678.3539289)
Lihui Liu, Boxin Du, Jiejun Xu, Yinglong xia, Hanghang Tong

8. ABM: Attention-based Message Passing Network for Knowledge Graph Completion. BigData 2022 [paper](https://ieeexplore.ieee.org/document/10021003)
Weikai Xu, Lihui Liu, Hanghang Tong

7. KomPare: A Knowledge Graph Comparative Reasoning System. KDD 2021 [paper](https://dl.acm.org/doi/abs/10.1145/3447548.3467128)
Lihui Liu, Boxin Du, Fung Yi, Heng Ji, Jiejun Xu, Hanghang Tong

6. Neural-Answering Logical Queries on Knowledge Graphs. KDD 2021 [paper](https://dl.acm.org/doi/abs/10.1145/3447548.3467375)
Lihui Liu, Boxin Du, Heng Ji, Chengxiang Zhai, Hanghang Tong

5. Sylvester Tensor Equation for Multi-Way Association, KDD 2021 [paper](https://dl.acm.org/doi/abs/10.1145/3447548.3467336)
Boxin Du, Lihui Liu, and Hanghang Tong

4. Dynamic Knowledge Graph Alignment, AAAI 2021 [paper](https://ojs.aaai.org/index.php/AAAI/article/view/16585)
Yuchen Yan, Lihui Liu, Hanghang Tong

3. A Knowledge Graph Reasoning Prototype. NeurIPS demo 2020 
Lihui Liu, Hanghang Tong

2. CANON: Complex Analytics of Network of Networks for Modeling Adversarial Activities. BigData 2020
S. Roach, C. Ni, A. Kopylov, T. Lu, J. Xu, S. Zhang, B. Du, Dawei Zhou, Jun Wu, Lihui Liu, Yuchen Yan, Jingrui He, Hanghang Tong

1. Approximated Attributed Subgraph Matching. BigData 2019 [paper](https://ieeexplore.ieee.org/document/9006525)
Lihui Liu, Boxin Du, Jiejun Xu, Hanghang Tong

Journals

1. Knowledge Graph Comparative Reasoning for Fact Checking: Problem Definition and Algorithms. 
   Data Engineering 2022
   Lihui Liu, Ruining Zhao, Boxin Du, Yi Ren Fung, Heng Ji, Jiejun Xu, Hanghang Tong

Conference Tutorials

1. Knowledge Graph Reasoning and Its Applications. KDD 2023. [website](https://sites.google.com/view/kg-reasoning/home)
   Lihui Liu, Hanghang Tong

2. New Frontiers of Knowledge Graph Reasoning: Recent Advances and Future Trends. WWW 2024
   Lihui Liu, Zihao Wang, Jiaxin Bai, Yangqiu Song, Hanghang Tong

Invited Talk

1. Knowledge Graph Reasoning for Biomedicine Applications, BDSC(The Biomedical
   Data Science Convention ForIndustry Discipline Development), Fall 2023.

2. Knowledge Graph Reasoning and Its Applications. Virginia Tech, Spring 2024.

Teaching Experience

1. Teaching Assistant, University of Illinois at Urbana-Champaign
CS512: Data Mining Principles, Prof. Hanghang Tong, Fall 2022.

Services

* Program Committee: IJCAI (2020-2023), CIKM (2020-2023), AAAI (2021), WSDM (2022-2023), WWW (2023-2024)
* Program Committee: KDD(2023), KDD(2024), NeurIPS(2024), CIKM(2024)
* SPC: AAAI (2022)

Industrial Experience

* Amazon: Alexa AI-Natural Understanding (Manager: Vidit Bansal).   2023/05 – 2023/07
    Job title: Applied scientist intern

* Amazon: Alexa AI-Natural Understanding (Manager: Vidit Bansal).   2022/06 – 2022/08
    Job title: Applied scientist intern

Honors and Awards

SDM Doctoral Forum Travel Award
CS PhD Fellowship 
Mavis Future Faculty Fellowship
Conference Presentation Award
Conference Presentation Award
BigData Student Travel Award