About me
I am a second-year Master student at the Joint Graduate School (Double degree) of Southeast University and Monash University. My graduate advisor is Professor Guilin Qi. I received my Bachelor’s degree from Hefei University in June 2022. I expect to receive a Master by research degree from Southeast University and a Master by course degree from Monash University in June 2025.
My research areas include Natural Language Processing (NLP) and Knowledge Graphs (KG). Currently, my main research focus is on enhancing the performance of LLMs using hybrid data (such as graphs and tables), comprehensively evaluating the performance of LLMs in question-answering tasks, and understanding and processing tabular data with LLMs. Additionally, I am also highly interested in multimodal (vision, language, and speech) large models.
I am currently seeking Ph.D. positions for Fall 2025 admission. If you are interested in my profile, please feel free to email me.
It is worth emphasizing that I would be willing to change my research topic in the early stages of my PhD based on the guidance of my advisor and the focus of the group or lab, and then commit to excelling in it.
Education
Southeast University , 09/2022 - present
- M.S. in Artificial Intelligence. Advisor: Guilin Qi
Monash University , 09/2022 - present
- M.S. in Artificial Intelligence.
Hefei University , 09/2017 - 06/2022
- B.S. in Electronic and Information Engineering
Publications
(* Refers to the authors having the equal contribution, and should be considered as co-first authors.)
Dehai Min*, Nan Hu*, Rihui Jin, Nuo Lin, Jiaoyan Chen, Yongrui Chen, Yu Li et al. Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data (NAACL 2024, industry track paper, Oral).
Yiming Tan*, Dehai Min*, Yu Li, Wenbo Li, Nan Hu, Yongrui Chen, and Guilin Qi. Can ChatGPT replace traditional KBQA models? An in-depth analysis of the question answering performance of the GPT LLM family (ISWC 2023, long paper, Oral) , Code
Nan Hu, Yike Wu, Guilin Qi, Dehai Min, Jiaoyan Chen, Jeff Z. Pan, and Zafar Ali. An empirical study of pre-trained language models in simple knowledge graph question answering (WWW 2023) , Code
Jiaqi Li, Chuanyi Zhang, Miaozeng Du, Dehai Min, Yongrui Chen, and Guilin Qi. Three stream based multi-level event contrastive learning for text-video event extraction (EMNLP 2023, long paper, Oral)
Yu Li, Shenyu Zhang, Rui Wu, Xiutian Huang, Yongrui Chen, Wenhao Xu, Guilin Qi, and Dehai Min. MATEval: A Multi-Agent Discussion Framework for Advancing Open-Ended Text Evaluation (DASFAA 2024)
Rihui Jin, Yu Li, Guilin Qi, Nan Hu, Yuan-Fang Li, Jiaoyan Chen, Jianan Wang, Yongrui Chen, and Dehai Min. HGT: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding (preprint 2024.03).
Work in progress
- Yiming Tan*, Dehai Min*, Huikang Hu, Nuo Lin, Guilin Qi, Sheng Bi et al. ELLMKGQA: Evaluation Framework of Large-language Model as Knowledge Graph on Question-Answering (submitted, under review).
Services
Reviewer: ISWC 2024
Competitions
( I was an active participant in programming competitions during my undergraduate years. )
- ACM-ICPC (International Collegiate Programming Contest) , Asian Regional Contest (Shanghai Site and others), 2019-2020, Silver Medal. individual / team
- CCPC-Finals (China Collegiate Programming Contest National Finals), 2019, 21st place, Silver Medal
- 16th Baidu Star Programming Contest, National Semi-Finals, 2019, 154th place (154/13900+)
- Anhui Province Collegiate Programming Contest, First Prize (2 times, 2019, 2020), Champion (1 time, 2020)
- Codeforces Rating: 2108 (Master), link
