Lihui Liu

Lihui Liu

Assistant Professor

Publications

Books

  1. Neural Symbolic Knowledge Graph Reasoning: A Pathway Towards Neural Symbolic AI. Springer, 2026. Lihui Liu, Hanghang Tong.

Journals

  1. Unifying Knowledge in Agentic LLMs: Concepts, Methods, and Recent Advancements. KDD Exploration, 2025. Lihui Liu, Kai Shu.
  2. Neural-Symbolic Reasoning over Knowledge Graphs: A Survey from a Query Perspective. KDD Exploration, 2025. Lihui Liu, Zihao Wang, Hanghang Tong.
  3. 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.

Preprint

  1. Personalized Large Language Models for Healthcare: A Comprehensive Survey
  2. LLM Agents for Healthcare: Concepts, Methods, and Applications
  3. A Survey of Large Language Models in Education: Perspectives from Students and Teachers
  4. A Survey of Unifying Large Language Models with Graph Learning: Concepts, Methods, and Recent Advancements for Text-attributed Graph

  5. A Survey of Process Reward Models in the Lifecycle of Large Language Models

  6. Universal Knowledge Base: A New Generation of Knowledge Management in the Era of Large Language Models
  7. HiKGC: Hyper-Relational Knowledge Graphs Completion with Neural Logical Operators

  8. Robust Conformal Consensus: Multi-Agent LLM-as-a-Judge Interval Evaluation with Conformal Prediction

  9. Scaling Enterprise Agent Deployment: A Survey of LLM-Based Operational Grounding Construction
  10. Reinforcement Learning for Large Language Model Post-Training, Reasoning, and Data Generation: A Survey

Conferences

  1. RLKGC: Reinforcement Learning Retrieval with Large Language Models for Knowledge Graph Completion. PAKDD, 2026. Urshi Barua Teya, Kai Shu, Lihui Liu.
  2. Neural-Symbolic Logic Query Answering in Non-Euclidean Space. PAKDD, 2026. Lihui Liu.
  3. Prompt-tuning with Attribute Guidance for Low-resource Entity Matching. PAKDD, 2026. Lihui Liu, Carl Yang.
  4. MixRAG: Mixture-of-Experts Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. WWW, 2026. Lihui Liu, Jiayuan Ding, Subhabrata Mukherjee, Carl Yang.
  5. MORGAN: To Bridge Mixture of Experts and Spectral Graph Neural Network. AAAI, 2026. Lihui Liu, Yuchen Yan.
  6. HyperKGR: Knowledge Graph Reasoning in Hyperbolic Space with Graph Neural Network Encoding Symbolic Path. EMNLP, 2025. Lihui Liu.
  7. Monte Carlo Tree Search for Graph Reasoning in Large Language Model Agents. CIKM, 2025. Lihui Liu.
  8. Few-Shot Knowledge Graph Completion via Transfer from Similar Tasks. CIKM, 2025. Lihui Liu, Zihao Wang, Dawei Zhou, Ruijie Wang, Yuchen Yan, Bo Xiong, Sihong He, Hanghang Tong.
  9. EviNet: Towards Open-World Graph Learning via Evidential Reasoning Network. KDD, 2025. Weijie Guan, Jian Kang, Lihui Liu, Dawei Zhou.
  10. R-KBQA: Revise-once correction for Generate-then-Retrieve KBQA. BigData, 2025. Bowen Huang, Lihui Liu.
  11. TUCKET: A Tensor Time Series Data Structure for Efficient and Accurate Factor Analysis over Time Ranges. VLDB, 2024. Ruzhong Qiu, Jun-Gi Jang, Xiao Lin, Lihui Liu, Hanghang Tong.
  12. Conversational Question Answering with Reformulations over Knowledge Graph. ACL 2024 Findings. Lihui Liu, Blaine Hill, Boxin Du, Hanghang Tong. paper
  13. Can contrastive learning refine embedding. ESWC, 2024. Lihui Liu, Jimha Kim, Vidit Bansal.
  14. Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform. WSDM, 2024. Blaine Hill, Lihui Liu, Hanghang Tong.
  15. PaCEr: Positional Embedding Meets Structural Embedding of Graph Representation Learning. WWW, 2024. Yuchen Yan, Yongyi Hu, Qinghai Zhou, Lihui Liu, Hanghang Tong.
  16. Reconciling Competing Sampling Strategies of Network Embedding. NeurIPS, 2023. Yuchen Yan, Baoyu Jing, Lihui Liu, Ruijie Wang, Jinning Li, Tarek Abdelzaher, Hanghang Tong. paper
  17. Knowledge Graph Question Answering with Ambiguous Query. WWW, 2023. Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong. paper
  18. Comparative Reasoning for Knowledge Graph Fact Checking. BigData, 2022. Lihui Liu, Houxiang Ji, Jiejun Xu, Hanghang Tong. paper
  19. Joint Knowledge Graph Completion and Question Answering. KDD, 2022. Lihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia, Hanghang Tong. paper
  20. ABM: Attention-based Message Passing Network for Knowledge Graph Completion. BigData, 2022. Weikai Xu, Lihui Liu, Hanghang Tong. paper
  21. KomPare: A Knowledge Graph Comparative Reasoning System. KDD, 2021. Lihui Liu, Boxin Du, Fung Yi, Heng Ji, Jiejun Xu, Hanghang Tong. paper
  22. Neural-Answering Logical Queries on Knowledge Graphs. KDD, 2021. Lihui Liu, Boxin Du, Heng Ji, Chengxiang Zhai, Hanghang Tong. paper
  23. Sylvester Tensor Equation for Multi-Way Association. KDD, 2021. Boxin Du, Lihui Liu, and Hanghang Tong. paper
  24. Dynamic Knowledge Graph Alignment. AAAI, 2021. Yuchen Yan, Lihui Liu, Hanghang Tong. paper
  25. A Knowledge Graph Reasoning Prototype. NeurIPS Demo, 2020. Lihui Liu, Hanghang Tong.
  26. 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.
  27. Approximated Attributed Subgraph Matching. BigData, 2019. Lihui Liu, Boxin Du, Jiejun Xu, Hanghang Tong. paper