📝 Publications
- [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.
- [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] 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
- [IJCAI 2024] 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
