I am currently a PhD student at School of College of Computer Science and Engineering, Southeast University, Nanjing, China, supervised by Prof. Peng Wang. Before that, I received my B.Eng. degree from Dalian University of Technology.

Currently, I am a Ph.D. student in the Department of Computer Science and Engineering of Southeast University. I am a member of the KGCODE Group, advised by Prof. Peng Wang and A.P. Wenjun Ke. Before that, I finished my M.S. career of Computer Technology at Southeast University in 2023. I obtained my B.S. degree of Computer Science and Technology from Dalian University of Technology in 2021.

Find me on Google Scholar , and Github!

Email: jiajliu@seu.edu.cn

My current research interests lie in knowledge disitllation (KD) large language models (LLMs) and knowledge graph (KGs). Currently, I am focused on Knowledge Distillation and Model Compression for LLMs.

• Southeast University, Nanjing, China. Mar. 2024 – Now.
  Ph.D. student of Computer Science and Technology, advised by Prof. Peng Wang

• Southeast University, Nanjing, China. Sep. 2021 - Jun. 2024
  M.S. student of Computer Technology, advised by Prof. Peng Wang and A.P. Wenjun Ke
  Avg-Score: 86.69, Ranking: 1/160.

• Dalian University of Technology, Dalian, China. Sep. 2017 - Jun. 2021
  B.S. degree of Computer Science and Technology
  Avg-Score: 89.50, Ranking: 11/125.

• [IJCAI 2024] Fast and Continual Knowledge Graph Embedding via Incremental LoRA. [paper] [code]
  Jiajun Liu, Wenjun Ke, Peng Wang, Ziyu Shang, et al.
• [AAAI 2024, Oral] Towards Continual Knowledge Graph Embedding via Incremental Distillation. [paper] [code]
  Jiajun Liu*, Wenjun Ke*, Peng Wang, Jiahao Wang, et al.
• [AAAI 2023] IterDE: An Iterative Knowledge Distillation Framework for Knowledge Graph Embeddings. [paper] [code]
  Jiajun Liu, Peng Wang, Ziyu Shang, Chenxiao Wu.
• [IJCAI 2025] Can Large Models Teach Student Models to Solve Mathematical Problems Like Human Beings? A Reasoning Distillation Method via Multi-LoRA Interaction. [paper] [code]
  Xinhe Li, Jiajun Liu, Peng Wang.
• [TKDE 2025] Learning Multi-Granularity and AdaptiveRepresentation for Knowledge Graph Reasoning. [paper]
  Ziyu Shang, Peng Wang, Jianghan Liu, Jiajun Liu, Guozheng Li, Zijie Xu, Zhizhao Luo, Xiye Chen, Wenjun Ke.
• [ACL 2025, Oral] Acquisition and Application of Novel Knowledge in Large Language Models. [paper]
  Ziyu Shang, Jianghan Liu, Zhizhao Luo, Peng Wang, Wenjun Ke, Jiajun Liu, Zijie Xu, Guozheng Li.
• [ACL 2025, Oral] LLM-Guided Semantic-Aware Clustering for Topic Modeling. [paper]
  Jianghan Liu, Ziyu Shang, Wenjun Ke, Peng Wang, Zhizhao Luo, Jiajun Liu, Guozheng Li, Yining Li.
• [ACL 2025 Findings] On the Consistency of Commonsense in Large Language Models. [paper]
  Guozheng Li, Peng Wang, Wenjun Ke, Zijie Xu, Jiajun Liu, Ziyu Shang.
• [NeurIPS 2024] Unveiling LoRA Intrinsic Ranks via Salience Analysis.
  Wenjun Ke, Jiahao Wang, Peng Wang, Jiajun Liu, Dong Nie, Guozheng Li, Yining Li.
• [ACL 2024 Findings] Boosting Textural NER with Synthetic Image and Instructive Alignment. [paper]
  Jiahao Wang, Wenjun Ke, Peng Wang, Hang Zhang, Dong Nie, Jiajun Liu, Guozheng Li, Ziyu Shang
• [IJCAI 2024] Domain-Hierarchy Adaptation via Chain of Iterative Reasoning for Few-shot Hierarchical Text Classification.[paper]
  Ke Ji, Peng Wang, Wenjun Ke, Guozheng Li, Jiajun Liu, Jingsheng Gao, Ziyu Shang
• [IJCAI 2024] Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors. [paper]
  Guozheng Li, Peng Wang, Jiajun Liu, Yikai Guo, Ke Ji, Ziyu Shang, Zijie Xu
• [IJCAI 2024] Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction. [paper]
  Guozheng Li, Peng Wang, Wenjun Ke, Yikai Guo, Ke Ji, Ziyu Shang, Jiajun Liu, Zijie Xu
• [IJCAI 2024] Empirical Analysis of Dialogue Relation Extraction with Large Language Model [paper]
  Guozheng Li, Zijie Xu, Ziyu Shang, Jiajun Liu, Ke Ji, Yikai Guo
• [IJCAI 2024] Learning Multi-Granularity and Adaptive Representation for Knowledge Graph Reasoning [paper]
  Ziyu Shang, Peng Wang, Wenjun Ke, Jiajun Liu, Hailang Huang, Guozheng Li, Chenxiao Wu, Jianghan Liu, Xiye Chen, Yining Li
• [IJCAI 2024] Incorporating Schema-Aware Description into Document-Level Event Extraction [paper][code]
  Zijie Xu, Peng Wang, Wenjun Ke, Guozheng Li, Jiajun Liu, Ke Ji, Xiye Chen, Chenxiao Wu
• [AAAI 2024, Oral] Ontofact: Unveiling fantastic fact-skeleton of llms via ontology-driven reinforcement learning [paper][code]
  Ziyu Shang, Wenjun Ke, Nanna Xiu, Peng Wang, Jiajun Liu, Yanhui Li, Zhizhao Luo, Ke Ji

• [Arxiv 2025] Unlearning of Knowledge Graph Embedding via Preference Optimization. [paper]
  Jiajun Liu, Wenjun Ke, Peng Wang, Yao He, Ziyu Shang, Guozheng Li, Zijie Xu, Ke Ji.

🎖 Honors and Awards

📖 Technique Experience

• 2025.03 - 2025.06, Teaching Assistant of Nature Language Models, Southeast University, Nanjing.

💻 Technique Competition