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ZHANG Qinggang (张庆刚) I am now a third-year PhD Candidate in DEEP Lab at The Hong Kong Polytechnic University, Department of Computing, supervised by Dr. Xiao HUANG. My research interests include Knowledge Graphs, Large Language Models, Graph Neural Networks, Recommender Systems, Question Answering, etc.

News

• [2024.03] I was invited as the PC member of KDD’24.

• [2024.02] Our paper MAIL was released which integrates the implicit knowledge in LLMs for VQA.

• [2024.02] Our papers SGU-SQL and DELLM was released which enhance LLMs for Text-to-SQL generation.

• [2024.01] Our paper KnowGPT was released which injects knowledge for LLMs with API only.

• [2023.09] I was invited to serve as the reviewer of TKDD.

• [2023.08] Our paper AEKE was accepted by TKDE.

• [2023.06] I passed the confirmation as a Ph.D. Candidate. Thanks to the distinguished panel members: Prof. Jiannong Cao, Prof. Qing Li, and Dr. Bo Li.

• [2023.05] I was invited to serve as the reviewer of TKDE.

• [2023.01] Our paper HamQA was accepted by WWW’23.

• [2022.08] Our paper KAEL was accepted by WSDM’23.

• [2022.05] Our paper CAGED was accepted by CIKM’22.

Publications

[†Co-first authors *Corresponding authors]

2024

• Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering.
  Junnan Dong, Qinggang Zhang, Huachi Zhou, Daochen Zha, Pai Zheng, Xiao Huang*
  Arxiv Preprint.

• Structure Guided Large Language Model for SQL Generation.
  Qinggang Zhang, Junnan Dong, Hao Chen, Wentao Li, Feiran Huang, Xiao Huang*
  Arxiv Preprint.

• Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM
  Zijin Hong, Zheng Yuan, Hao Chen, Qinggang Zhang, Feiran Huang, Xiao Huang*
  Arxiv Preprint.

• KnowGPT: Black-Box Knowledge Injection for Large Language Models.
  Qinggang Zhang†, Junnan Dong†, Hao Chen, Daochen Zha, Zailiang Yu, Xiao Huang*
  Arxiv Preprint.

2023

• Integrating Entity Attributes for Error-Aware Knowledge Graph Embedding.
  Qinggang Zhang, Junnan Dong, Qiaoyu Tan, Xiao Huang*
  IEEE Transactions on Knowledge and Data Engineering (TKDE 2023).

• Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs.
  Junnan Dong†, Qinggang Zhang†, Xiao Huang*, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang
  The Web Conference (WWW 2023).

• Error Detection on Knowledge Graphs with Triple Embedding.
  Yezi Liu, Qinggang Zhang, Mengnan Du, Xiao Huang, Xia Hu*
  The 31st European Signal Processing Conference (EUSIPCO 2023).

• Active Ensemble Learning for Knowledge Graph Error Detection.
  Junnan Dong, Qinggang Zhang, Xiao Huang*, Qiaoyu Tan, Daochen Zha, Zihao Zhao
  ACM International Conference on Web Search and Data Mining (WSDM 2023).

2022

• Contrastive Knowledge Graph Error Detection. (Slides, Code)
  Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang*, Yezi Liu, Linchuan Xu.
  ACM International Conference on Information and Knowledge Management (CIKM 2022).

• Constructing Low-Redundant and High-Accuracy Knowledge Graphs for Education.
  Wentao Li, Huachi Zhou, Junnan Dong, Qinggang Zhang, Qing Li, George Baciu, Jiannong Cao and Xiao Huang
  International Conference on Web-Based Learning (ICWL 2022).

Honors

• SIGIR Student Travel Grant in 2022

• Vector Scholarship in Artificial Intelligence in 2020-2021

• Outstanding graduate award (undergraduate in NWPU)

• National scholarships in 2015, 2017 and 2018

• First-class scholarships in every year of undergraduate

• The CCF Outstanding Undergraduate Award in 2016

Awards

• Champion in 2017 China Robot Competition

• Champion in the 2017 international Underwater Robot competition

• Honorable Mention in the 2017 Interdisciplinary Contest in Modeling

• Champion in “WRC2016” international Underwater Robot competition

• Champion at 21th FIRA RoboWorld Cup 2016,Beijing,China

• Champion in 2016 China Robot Competition