👨🏻‍🎓 Biography

I am a Ph.D. candidate at the School of Artificial Intelligence and Data Science, University of Science and Technology of China (USTC), and a member of State Key Laboratory of Cognitive Intelligence. My supervisor is 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 and Huawei - Cloud & AI, as an algorithm intern. I received my Bachelor degree from USTC in July, 2019, and majored in Electronic Information Engineering.

I am on the job market the next year! I will graduate with my Ph.D. degree in summer 2025. I am open to faculty/postdoctoral positions or related industry roles. Please get in touch!

Here are my Curriculum Vitae and Research Statement (November 2024).

👨🏻‍💻 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

• 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!

📝 Publications

†: Equal Contribution

Preprint

• Ye Liu, Jiajun Zhu, Kai Zhang, Haoyu Tang, Yanghai Zhang, Xukai Liu, Qi Liu, Enhong Chen.
  Detect, Investigate, Judge and Determine: A Novel LLM-based Framework for Few-shot Fake News Detection.[arxiv] [code].
• Haoyu Tang†, Ye Liu†, Xukai Liu, Kai Zhang, Yanghai Zhang, Qi Liu, Enhong Chen.
  Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models. [arxiv] [code].
• Aoran Gan, Ye Liu, Hongbo Gang, Kai Zhang, Qi Liu, Guoping Hu.
  Discover rather than Memorize: A Novel Benchmark for Relational Triple Extraction. [paper]
• Feng Hu, Kai Zhang, Ye Liu, Meikai Bao, Xukai Liu, Junyu Lu, Linbo Zhu, Qi Liu.
  Learnable Relational Knowledge Distillation Through Orthogonal Projection.

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. [arxiv] [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.

🎖 Honors and Awards

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

📖 Educations

• Septemper 2019 - now, Ph.D. Candidate, 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).

💻 Internships

• February 2023 - August 2023, ByteDance - AI LAB, Beijing, China.
• February 2019 - August 2019, Huawei - Cloud & AI, Hangzhou, China.

👨🏻‍🏫 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

• Conference Reviewer: ACL Rolling Review, ICLR.
• Journal Reviewer: IEEE TKDE, IEEE TBD.