I am a 5th-year Ph.D. student in Computer Science and Engineering at the University of Notre Dame, advised by Prof. Meng Jiang. Before that, I received my Master degree of ECE department at UIUC.

I am actively seeking industrial R&D opportunities, as well as Postdoctoral positions, beginning in 2024. I am happy to engage in discussions regarding potential opportunities!

Research Interest

• Knowledge Graph
• Natural Language Processing
• Large Language Models

What’s New

• [March 2024] The code of Chain-of-Layer is available now. Feel free to generate your own taxonomy!
• [February 2024] Two papers about (1) Entity Linking via leveraging LLMs (ChatEL (Coming Soon)) (2) Mathematical Reasoning (MinT) were accepted by LREC-COLING 2024. Huge congrats to Yifan Ding and Zhenwen Liang!
• [February 2024] Three papers about (1) Taxonomy Induction via prompting LLMs (Chain-of-Layer) (2) personalized LLMs (OPPU) (3) Entity Linking via leveraging LLMs (EntGPT) are available on Arxiv now!
• [October 2023] One paper was accepted by The EMNLP 2023.
• [April 2023] I am joining Tencent AI Lab as a full-time research intern this summer! I will work with Dr. Linfeng Song and Dr. Haitao Mi.
• [May 2022] One paper was accepted by The KDD 2022.
• [May 2021] One paper was accepted by The KDD 2021.
• [May 2021] Our ICSE 2021 paper was selected for an ACM SIGSOFT Distinguished Paper Award!

Recent Publications

• Qingkai Zeng, Yuyang Bai, Zhaoxuan Tan, Shangbin Feng, Zhenwen Liang, Zhihan Zhang, Meng Jiang. Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples, arXiv preprint arXiv:2402.07386 (2024). [PDF] [Code]

• Qingkai Zeng, Zhihan Zhang, Jinfeng Lin, Meng Jiang. Completing Taxonomies with Relation-Aware Mutual Attentions, In the Workshop on Mining and Learning with Graphs (MLG) in conjunction with the ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), 2023. [PDF]

• Qingkai Zeng, Jinfeng Lin, Wenhao Yu, Jane Cleland-Huang, Meng Jiang, Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations, In Proceedings of the ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), 2021 . [PDF]

• Qingkai Zeng, Wenhao Yu, Mengxia Yu, Tianwen Jiang, Tim Weninger, Meng Jiang, Tri-Train: Automatic Pre-fine Tuning between Pre-training and Fine-tune Training for SciNER, Findings of Empirical Methods on Natural Language Processing (EMNLP), 2020. [PDF]

• Qingkai Zeng, Mengxia Yu, Wenhao Yu, Jinjun Xiong, Yiyu Shi, Meng Jiang, Faceted Hierarchy: A New Graph Type to Organize Scientific Concepts and a Construction Method, In the Workshop on Graph-Based Natural Language Processing (TextGraphs) at Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019. [PDF]

• Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bin Yin, Meng Jiang. Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning, arXiv preprint arXiv:2402.04401 (2024). [PDF]

• Yifan Ding, Amrit Poudel, Qingkai Zeng, Tim Weninger, Balaji Veeramani, Sanmitra Bhattacharya. EntGPT: Linking Generative Large Language Models with Knowledge Bases, arXiv preprint arXiv:2402.06738 (2024). [PDF]

• Jinfeng Lin, Yalin Liu, Qingkai Zeng, Meng Jiang, Jane Cleland-Huang, Traceability Transformed: Generating More Accurate Links with Pre-Trained BERT Models, in Proceeding of IEEE/ACM International Conference on Software Engineering (ICSE), 2021. [PDF] (ACM SIGSOFT Distinguished Paper Award)

• Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, Meng Jiang, Boosting Factual Correctness of Abstractive Summarization with Knowledge Graph, In Proceedings of North American Chapter of the Association for Computational Linguistics (NAACL), 2021 . [PDF]

Contact

• Email: qzeng [at] nd [dot] edu
• Office: 355 Fitzpatrick Hall of Engineering
• Location: University of Notre Dame, Notre Dame, IN 46565