Ye LIU（刘烨）

Ye LIU（刘烨）

Ph.D., USTC (2025)
B.E., USTC (2019)

👨🏻‍🎓 Biography

I received my Ph.D. degree from the School of Artificial Intelligence and Data Science, University of Science and Technology of China (USTC) in April, 2025, under the supervision of Prof. Enhong Chen. Previously, I was a visiting Ph.D. student with Prof. Xiaofang Zhou at The Hong Kong University of Science and Technology (HKUST), and interned at ByteDance - AI LAB, as an algorithm intern. I received my Bachelor degree from USTC in July, 2019, and majored in Electronic Information Engineering.

Here is my Curriculum Vitae (April 2025).

👨🏻‍💻 Research Interest

My research interests encompass a wide range of subjects within the fields of Knowledge-aware Natural Language Processing (NLP), focusing on two main areas: (1) Knowledge Acquisition and (2) Knowledge Application. Recently, I am exploring a focused research direction of Knowledge-enhanced Large Language Models (LLMs). I have published more than 20 papers at the top international conferences/journals.

  • Knowledge Acquisition: Acquisition of knowledge concept, knowledge relation, knowledge linking and alignment using information extraction, crowd-sourcing, and LLM In-Context Learning (ICL) techniques.
  • Knowledge Application: Application of extracted knowledge in various NLP downstream tasks, including but not limited to: Hierarchical Text Classification (HTC), Multimodal Summarization with Multimodal Output (MSMO), Question Answering (QA), etc.
  • Knowledge-enhanced LLMs: Mitigate the hallucination problem and elicit complex reasoning ability of LLMs with the integration of internal/external knowledge, mainly through the approaches such as pre-training and Retrieval-Augmented Generation (RAG).

🔥 News

  • 3/2025:  🎉🎉 Successfully defended my Ph.D. dissertation!!! [slides]
  • 1/2025:  🎉🎉 Two papers accepted to DASFAA conference!
  • 11/2024:  🎉🎉 Finished my visiting at HKUST! Grateful to my advisor and all I’ve met here!!!
  • 10/2024:  🎉🎉 After four years review, One patent has been granted!
  • 9/2024:  🎉🎉 One paper accepted to EMNLP conference! See you in Miami!
  • 7/2024:  🎉🎉 One paper accepted to CIKM conference!
  • 5/2024:  🎉🎉 One paper accepted to ACL conference!

🎤 Talks

  • March 3, 2025
    📌 Title: Research on Knowledge Concept Mining and Application Methods for Trustworthy Natural Language Processing. [slides]
    📍 Location: University of Science and Technology of China.
  • September 19, 2024
    📌 Title: Knowledge-aware NLP Techniques for Trustworthy AI Systems. [poster] [slides]
    📍 Location: Weill Cornell Medicine, Cornell University (Online).

📝 Publications

†: Equal Contribution

Preprint

  • Ye Liu, Jiajun Zhu, Xukai Liu, Haoyu Tang, Yanghai Zhang, Kai Zhang, Xiaofang Zhou, Enhong Chen.
    Detect, Investigate, Judge and Determine: A Knowledge-guided Framework for Few-shot Fake News Detection.[arxiv] [code]
  • Haoyu Tang†, Ye Liu†, Xi Zhao, Xukai Liu, Yanghai Zhang, Kai Zhang, Xiaofang Zhou, Enhong Chen.
    Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models. [arxiv] [code]
  • Xukai Liu, Ye Liu, Shiwen Wu, Yanghai Zhang, Yihao Yuan, Kai Zhang, Qi Liu.
    Know³-RAG: A Knowledge-aware RAG Framework with Adaptive Retrieval, Generation, and Filtering. [arxiv] [code]

2025

  • Aoran Gan, Ye Liu, Hongbo Gang, Kai Zhang, Qi Liu, Guoping Hu.
    From Memorization to Discovery: A Novel Benchmark for Relational Triple Extraction. [paper] [data]
    The 30th International Conference on Database Systems for Advanced Applications (DASFAA), 2025.
  • Feng Hu, Kai Zhang, Ye Liu, Meikai Bao, Xukai Liu, Junyu Lu, Linbo Zhu, Qi Liu.
    Learnable Relational Knowledge Distillation For Language Model Compression. [paper] [code]
    The 30th International Conference on Database Systems for Advanced Applications (DASFAA), 2025.

2024

  • Ye Liu, Kai Zhang*, Aoran Gan, Linan Yue, Feng Hu, Qi Liu, Enhong Chen.
    Empowering Few-Shot Relation Extraction with The Integration of Traditional RE Methods and Large Language Models. [paper] [code]
    The 29th International Conference on Database Systems for Advanced Applications (DASFAA), 2024.
  • Yanghai Zhang, Ye Liu, Shiwei Wu, Kai Zhang*, Xukai Liu, Qi Liu, Enhong Chen.
    Leveraging Entity Information for Cross-Modality Correlation Learning: The Entity-Guided Multimodal Summarization. [paper] [code]
    Findings of the 62nd annual meeting of the Association for Computational Linguistics (ACL-Findings), 2024.
  • Xukai Liu, Ye Liu, Kai Zhang, Kehang Wang, Qi Liu, Enhong Chen.
    OneNet: A Fine-Tuning Free Framework for Few-Shot Entity Linking via Large Language Model Prompting. [paper] [code]
    The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
  • Linan Yue, Qi Liu, Ye Liu, Weibo Gao, et al.
    Cooperative Classification and Rationalization for Graph Generalization. [arxiv] [code]
    The ACM Web Conference, 2024 (WWW), 2024.
  • Linan Yue, Qi Liu, Weibo Gao, Ye Liu, Kai Zhang, Yichao Du, Li Wang, et al.
    Federated Self-Explaining GNNs with Anti-shortcut Augmentations. [paper] [code]
    The 41st International Conference on Machine Learning (ICML), 2024.
  • Kehang Wang, Ye Liu, Kai Zhang, Qi Liu, Yankun Ren, Xinxing Yang, Longfei Li, Jun Zhou.
    QoMRC: Query-oriented Machine Reading Comprehension Framework for Aspect Sentiment Triplet Extraction. [paper]
    The 29th International Conference on Database Systems for Advanced Applications (DASFAA), 2024.
  • Zhijun Dong, Likang Wu, Kai Zhang, Ye Liu, Yanghai Zhang, Zhi Li, Hongke Zhao and Enhong Chen.
    FZR: Enhancing Knowledge Transfer via Shared Factors Composition in Zero-Shot Relational Learning. [paper]
    The 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024.
  • Linan Yue, Qi Liu, Yichao Du, Weibo Gao, Ye Liu, et al.
    FedJudge: Federated Legal Large Language Model. [arxiv] [code]
    The 29th International Conference on Database Systems for Advanced Applications (DASFAA), 2024.
  • Enhong Chen, Qi Liu, Jianhui Ma, Ye Liu, Han Wu, et al.
    Automatic Extraction Method for Technical Phrases in Patents. [patent]
    Patent Number: ZL 2020 1 0887328.5, China National Intellectual Property Administration, Granted: April 2, 2024.

2023

  • Ye Liu, Kai Zhang, Zhenya Huang, Kehang Wang, Yanghai Zhang, Qi Liu, Enhong Chen.
    Enhancing Hierarchical Text Classification through Knowledge Graph Integration. [paper] [code]
    Findings of the 61st annual meeting of the Association for Computational Linguistics (ACL-Findings), 2023.
  • Ye Liu, Han Wu, Zhenya Huang, Hao Wang, Yuting Ning, Jianhui Ma, Qi Liu, Enhong Chen*.
    TechPat: Technical Phrase Extraction for Patent Mining. [paper] [code]
    ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2023.
  • Xukai Liu, Kai Zhang*, Ye Liu, Enhong Chen, Zhenya Huang, Linan Yue, Jiaxian Yan.
    RHGH: Relation-gated Heterogeneous Graph Network for Entity Alignment in Knowledge Graphs. [paper] [code]
    Findings of the 61st annual meeting of the Association for Computational Linguistics (ACL-Findings), 2023.
  • Meikai Bao, Qi Liu*, Kai Zhang, Ye Liu, Linan Yue, Longfei Li, Jun Zhou.
    Keep Skills in Mind: Understanding and Implementing Skills in Commonsense Question Answering. [paper] [code]
    The 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
  • Kehang Wang, Qi Liu*, Kai Zhang, Ye Liu, Hanqin Tao, Zhenya Huang, Enhong Chen.
    Class-Dynamic and Hierarchy-Constrained Network for Entity Linking. [paper] [code]
    The 28th International Conference on Database Systems for Advanced Applications (DASFAA), 2023.
  • Xin Jin, Qi Liu*, Linan Yue, Ye Liu, Lili Zhao, Weibo Gao, Zheng Gong, Kai Zhang, Haoyang Bi.
    Diagnosis then Aggregation: An Adaptive Ensemble strategy for Keyphrase Extraction. [paper] [code]
    CAAI International Conference on Artificial Intelligence (CICAI), 2023. (Finalist of Best Paper Award!)

2022

  • Huijie Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Chunli Liu, Minglei Li, Qi Liu, Enhong Chen.
    A Hierarchical Interactive Multi-channel Graph Neural Network for Technological Knowledge Flow Forecasting. [paper]
    Knowledge and Information Systems (KAIS), 2022.
  • Guanqi Zhu, Hanqing Tao, Han Wu, Liyi Chen, Ye Liu, Qi Liu, Enhong Chen*.
    Text Classification via Learning Semantic Dependency and Association. [paper]
    The 2022 IEEE World Congress on Computational Intelligence - IJCNN (IJCNN), 2022.

2021

  • Yixiao Ma, Shiwei Tong, Ye Liu, Likang Wu, Qi Liu, Enhong Chen*, Wei Tong, Zi Yan.
    Enhanced Representation Learning for Examination Papers with Hierarchical Document Structure. [paper]
    The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021.
  • Songtao Fang, Zhenya Huang*, Ming He, Shiwei Tong, Xiaoqing Huang, Ye Liu, Jie Huang, Qi Liu.
    Guided Attention Network for Concept Extraction. [paper]
    The 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021.
  • Huijie Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Chunli Liu, Qi Liu, Enhong Chen.
    Technological Knowledge Flow Forecasting through A Hierarchical Interactive Graph Neural Network. [paper]
    IEEE International Conference on Data Mining (ICDM), 2021.
  • Yuting Ning, Ye Liu, Zhenya Huang, Haoyang Bi, Qi Liu, Enhong Chen*, Dan Zhang.
    Stable and Diverse: A Unified Approach for Computerized Adaptive Testing. [paper]
    The 7th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 2021.
  • Lili Zhao, Linan Yue, Yanqing An, Ye Liu, Kai Zhang, Weidong He, Yanmin Chen, Qi Liu*.
    Legal Judgment Prediction with Multiple Perspectives on Civil Cases. [paper]
    The 1st CAAI International Conference on Artificial Intelligence (CICAI), 2021.

2020

  • Ye Liu, Han Wu, Zhenya Huang, Hao Wang, Jianhui Ma, Qi Liu, Enhong Chen*, Hanqing Tao and Ke Rui.
    Technical Phrase Extraction for Patent Mining: A Multi-level Approach. [paper] [code]
    The 2020 IEEE International Conference on Data Mining (ICDM), 2020.

📖 Educations

  • Septemper 2019 - April 2025, Ph.D., University of Science and Technology of China (USTC), Supervisor: Prof. Enhong Chen.
  • May 2024 - November 2024, Visiting Ph.D. Student, Hong Kong University of Science and Technology (HKUST), Supervisor: Prof. Xiaofang Zhou.
  • Septemper 2015 - June 2019, B.E., University of Science and Technology of China (USTC).

💻 Industrial Experience

  • February 2023 - August 2023, ByteDance - AI LAB, Beijing, China.

🎖 Honors and Awards

  • 2019, 2020, 2022 - 2024:  🏅 Graduate Student First-class Academic Scholarship.
  • 2023:  🏅 CICAI Finalist of Best Paper Award (Top-3).
  • 2021:  🏅 Graduate Student Second-class Academic Scholarship.
  • 2016:  🏅 National Scholarship.

👨🏻‍🏫 Teaching

  • COMP6110P.02: Machine Learning and Knowledge Discovery (Fall 2021).
  • CS1001A.13: Computer Programming A (Fall 2020).
  • 011X3001: Introduction to Data Science (Fall 2019).
  • 011164.01: Computer Programming I (Fall 2018).

🔖 Academic Service

  • Area Chairs: ACL Rolling Review.
  • Program Commitee Members: WWW.
  • Conference Reviewer: ACL Rolling Review, ICLR.
  • Journal Reviewer: IEEE TKDE, IEEE TBD, JCST.