Short Bio

Currently, I am an assistant researcher (Yuxiu Young Scholar) of Websoft Research Group at Department of Computer Science and Technology, Nanjing University. I received my B.Sc. degree in College of Computer and Information in June 2016 from Hohai University. In the same year, I was admitted to study for a M.Sc. degree in Nanjing University without entrance examination. In Sept. 2018, I started my Ph.D. degree under the supervision of Prof. Yuzhong Qu and Prof. Wei Hu. I obtained my PhD degree in March 2023.

Research Interest

My research interests include knowledge graph representation learning and its applications (e.g., entity alignment, relation prediction and type inference), applied machine learning and deep learning (recurrent neural networks, multi-relational graph neural networks, etc.).

Publications

[NAACL'24] Xindi Luo, Zequn Sun, Jing Zhao, Zhe Zhao, Wei Hu. KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation. To appear in Proc. of the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics. [code]

[KBS'24] Lingbing Guo, Zhuo Chen, Jiaoyan Chen, Yichi Zhang, Zequn Sun, Zhongpo Bo, Yin Fang, Xiaoze Liu, Huajun Chen, Wen Zhang. Distributed Representations of Entities in Open-World Knowledge Graphs. Accepted by Knowledge-Based Systems. [code]

[ICDE'24] Xiaobin Tian, Zequn Sun^#, Wei Hu^#. Generating Explanations to Understand and Repair Embedding-based Entity Alignment. To appear in Proc. of the 40th IEEE International Conference on Data Engineering. [code]

[NeurIPS'23] Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen. Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems. In Proc. of the 37th Conference on Neural Information Processing Systems. [code]

[KDD'23] Zequn Sun, Jiacheng Huang, Jinghao Lin, Xiaozhou Xu, Qijin Chen, Wei Hu. Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs. In Proc. of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. [code]

[ICML'23] Zequn Sun, Jiacheng Huang, Xiaozhou Xu, Qijin Chen, Weijun Ren, Wei Hu. What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings. In Proc. of the 40th International Conference on Machine Learning. [code]

[IJCAI'23] Yu-Xuan Huang, Zequn Sun, Guangyao Li, Xiaobin Tian, Wang-Zhou Dai, Wei Hu, Yuan Jiang, Zhi-Hua Zhou. Enabling Abductive Learning to Exploit Knowledge Graph. In Proc. of the 32nd International Joint Conference on Artificial Intelligence. [code]

[TNNLS'23] Guangyao Li, Zequn Sun, Wei Hu, Gong Cheng and Yuzhong Qu. Position-aware Relational Transformer for Knowledge Graph Embedding. IEEE Transactions on Neural Networks and Learning Systems. [code]

[SIGMOD'23] Jiacheng Huang, Zequn Sun, Qijin Chen, Xiaozhou Xu, Weijun Ren and Wei Hu. Deep Active Alignment of Knowledge Graph Entities and Schemata. In Proc. of the International Conference on Management of Data. [code]

[JOS'23] Zequn Sun, Yuanning Cui, Wei Hu. Lifelong Representation Learning on Multi-sourced Knowledge Graphs via Linked Entity Replay. Journal of Software (in Chinese). [code]

[AAAI'23] Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han and Wei Hu. Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs. In Proc. of the 37th AAAI Conference on Artificial Intelligence. [code]

[TKDE'22] Zequn Sun, Wei Hu, Chengming Wang, Yuxin Wang, Yuzhong Qu. Revisiting Embedding-based Entity Alignment: A Robust and Adaptive Method. IEEE Transactions on Knowledge and Data Engineering. [code]

[CIKM'22] Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, Jianfeng Qu and Xiaofang Zhou. Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding. In Proc. of the 31st ACM International Conference on Information and Knowledge Management. [code]

[CIKM'22] Yang Liu, Zequn Sun, Guangyao Li and Wei Hu. I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning. In Proc. of the 31st ACM International Conference on Information and Knowledge Management. [code]

[CIKM'22] Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han and Wei Hu. Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities. In Proc. of the 31st ACM International Conference on Information and Knowledge Management. [code]

[ISWC'22] Xindi Luo, Zequn Sun*, Wei Hu. μKG: A Library for Multi-source Knowledge Graph Embeddings and Applications. In Proc. of the 21st International Semantic Web Conference. [code]

[ISWC'22] Yuxin Wang, Yuanning Cui, Wenqiang Liu, Zequn Sun, Yiqiao Jiang, Kexin Han and Wei Hu. Facing Changes: Continual Entity Alignment for Growing Knowledge Graphs. In Proc. of the 21st International Semantic Web Conference. [code]

[ICML'22] Lingbing Guo, Qiang Zhang, Zequn Sun, Mingyang Chen, Wei Hu, Huajun Chen. Understanding and Improving Knowledge Graph Embedding for Entity Alignment. In Proc. of the 39th International Conference on Machine Learning. [code]

[NAACL'22] Juncheng Liu, Zequn Sun, Bryan Hooi, Yiwei Wang, Dayiheng Liu, Baosong Yang, Xiaokui Xiao, Muhao Chen. Dangling-Aware Entity Alignment with Mixed High-Order Proximities. In Findings of NAACL 2022. [code]

[AAAI'22] Kexuan Xin, Zequn Sun, Wen Hua, Bing Liu, Wei Hu, Jianfeng Qu, Xiaofang Zhou. Ensemble Semi-supervised Entity Alignment via Cycle-teaching. In Proc. of the 36th AAAI Conference on Artificial Intelligence. [code]

[WSDM'22] Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, Xiaofang Zhou. Informed Multi-context Entity Alignment. In Proc. of the 15th ACM International Conference on Web Search and Data Mining. [code]

[ACL'21] Zequn Sun, Muhao Chen, Wei Hu. Knowing the No-match: Entity Alignment with Dangling Cases. In Proc. of the 59th Annual Meeting of the Association for Computational Linguistics. [code][DBP2.0]

[EMNLP'20] Zequn Sun, Muhao Chen, Wei Hu, Chengming Wang, Jian Dai, Wei Zhang. Knowledge Association with Hyperbolic Knowledge Graph Embeddings. In Proc. of the 2020 Conference on Empirical Methods in Natural Language Processing. [code]

[VLDB'20] Zequn Sun, Qingheng Zhang, Wei Hu, Chengming Wang, Muhao Chen, Farahnaz Akrami, Chengkai Li. A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs. In Proc. of the VLDB Endowment, Vol. 13, No. 11. [code][data]

[AAAI'20] Zequn Sun*, Chengming Wang*, Wei Hu, Muhao Chen, Jian Dai, Wei Zhang, Yuzhong Qu. Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation. In Proc. of the 34th AAAI Conference on Artificial Intelligence. [code]

[ISWC'19] Zequn Sun, Jiacheng Huang, Wei Hu, Muchao Chen, Lingbing Guo, Yuzhong Qu. TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs. In Proc. of the 18th International Semantic Web Conference. [code]

[IJCAI'19] Qingheng Zhang*, Zequn Sun*, Wei Hu, Muchao Chen, Lingbing Guo, Yuzhong Qu. Multi-view Knowledge Graph Embedding for Entity Alignment. In Proc. of the 28th International Joint Conference on Artificial Intelligence. [code]

[ICML'19] Lingbing Guo, Zequn Sun, Wei Hu. Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs. In Proc. of the 36th International Conference on Machine Learning. [Supplementary][code]

[IJCAI'18] Zequn Sun, Wei Hu, Qingheng Zhang, Yuzhong Qu. Bootstrapping Entity Alignment with Knowledge Graph Embedding. In Proc. of the 27th International Joint Conference on Artificial Intelligence. [code][DWY100K]

[ISWC'17] Zequn Sun, Wei Hu, Chengkai Li. Cross-Lingual Entity Alignment via Joint Attribute-Preserving Embedding. In Proc. of the 16th International Semantic Web Conference. [website][code][DBP15K]

[ISWC'16] Wei Hu, Haoxuan Li, Zequn Sun, Xinqi Qian, Lingkun Xue, Ermei Cao, Yuzhong Qu. Clinga: Bringing Chinese Physical and Human Geography in Linked Open Data. In Proc. of the 15th International Semantic Web Conference. [data]

Awards & Honors

2023: Yuxiu Young Scholars Program of Nanjing University
2023: Outstanding Graduate of Jiangsu Province
2023: Most Influential Scholar Award Honorable Mention (in the field of Knowledge Engineering between 2013 and 2022, by Aminer)
2022: BootEA was selected as one of the Most Influential IJCAI-2018 Papers by Paper Digest (Version: 2022-05).
2021: MultiKE was selected as one of the Most Influential IJCAI-2019 Papers by Paper Digest (Version: 2021-02).
2021: Program A for outstanding PhD candidate of Nanjing University (only 12 students).
2021: Most Influential Scholar Award Honorable Mention (in the field of Knowledge Engineering between 2011 and 2020, by Aminer)
2020: National Scholarship (for Ph.D. students).
2020: VLDB Student Registration Support.
2019: Huawei Scholarship (for Ph.D. students).
2019: IJCAI Travel Grant.
2018: National Scholarship (for Ph.D. students).
2017: Huawei Scholarship (for master students).
2017: First-Class Academic Scholarship of Nanjing University.
2017: ISWC Student Travel Grant.
2016: Outstanding Undergraduate Student of Hohai University.
2014: National Scholarship (for undergraduate students).

Teaching Assistant

Knowledge Engineering (For graduate students, Spring, 2021)
Introduction to Databases (For undergraduate students, Autumn, 2019)
Introduction to Databases (For undergraduate students, Autumn, 2018)

PC Member

2024: AAAI, ICLR, ESWC, ICML, ARR
2023: AAAI, ICLR, ACL Rolling Review, ESWC, IJCAI, ICML, ISWC, CCKS, NLPCC, NeurIPS, EMNLP
2022: ICLR, AAAI, ACL Rolling Review, IJCAI, ICML, ISWC, NeurIPS, EMMLP, CCKS
2021: AAAI, ICLR, EACL, IJCAI (senior PC), ICML, ACL, ISWC, EMNLP, NeurIPS
2020: AAAI, ACL, EMNLP, ISWC, NeurIPS.
Before 2020: ISWC 2019 (Posters and Demos Track), CCKS 2018.

Invited Reviewer for Journals

Big Data Research, Data Mining and Knowledge Discovery, Neurocomputing, Journal of Web Semantics, IEEE Transactions on Audio, Speech, and Language Processing, Pattern Recognition, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks and Learning Systems, Neural Networks