Zhaoxuan Tan  「谭兆轩」

Hi there, thanks for visiting my website! I am a fourth-year undergraduate student at Xi'an Jiaotong University, majoring in computer science and technology.

My research focuses on knowledge base, social network analysis, natural language processing, and graph neural networks advised by Prof. Minnan Luo. I'm serving as the director of LUD lab, the premiere undergraduate research group @ XJTU. In 2022, I spent a summer at KEG @ THU to work with Prof. Yuxiao Dong.

I have the fortune to work with brilliant mentors, collaborators, and advisors during my undergraduate and I am truly grateful for their guidance and help. If you feel like I can be of some help to your research career, welcome to reach out, I'd be happy to chat.
Also, please feel free to drop me an Email for any form of communication or collaboration!😆

Email:  ztan3 [at] nd [dot] edu  /  tanzx9 [at] gmail [dot] com

CV  /  Google Scholar  /  Semantic Scholar  /  Twitter  /  Github

profile photo
What's New

  • [2023.03] I will join the University of Notre Dame to work with Prof. Meng Jiang this fall. Thank you for seeing my potential and looking forward to the incoming PhD journey!🥳
  • [2023.02] BotPercent is alive on ArXiv, welcome to check out our work!
  • [2023.01] KRACL was accepted by WWW 2023, cheers!🍻

Research Interests

My research interests lie in the intersection of graph mining (especially knowledge graphs and social networks) and natural language processing, with a special focus on these two topics:

  • Knowledge base representation & reasoning and its integration with NLP.
  • Computation (NLP / DM) for the social good.

Publications (* indicates equal contribution)
3DSP BotPercent: Estimating Twitter Bot Populations from Groups to Crowds
Zhaoxuan Tan*, Shangbin Feng*, Melanie Sclar, Herun Wan, Minnan Luo, Yejin Choi, Yulia Tsvetkov
arXiv preprint arXiv:2302.00381, 2023.
demo / tweet

We introduce the concept of community-level Twitter bot detection and develope BotPercent, a multi-dataset, multi-model Twitter bot detection pipeline. Utilizing BotPercent, we investigate the presence of bots in various Twitter communities and discovered that bot distribution is heterogeneous in both space and time.

3DSP KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion
Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo
Proceedings of The Web Conference (WWW), 2023.
code / talk

We adopt contrastive learning and knowledge relational attention network to alleviate the widespread sparsity problem in knowledge graphs.

3DSP TwiBot-22: Towards Graph-Based Twitter Bot Detection
Shangbin Feng*, Zhaoxuan Tan*, Herun Wan*, Ningnan Wang*, Zilong Chen*, Binchi Zhang*, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo
Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2022.
website / GitHub / bibtex / poster

We present TwiBot-22, the largest graph-based Twitter bot detection benchmark to date, which provides diversified entities and relations in Twittersphere and has considerably better annotation quality.

3DSP PAR: Political Actor Representation Learning with Social Context and Expert Knowledge
Shangbin Feng, Zhaoxuan Tan, Zilong Chen, Peisheng Yu, Qinghua Zheng, Xiaojun Chang, Minnan Luo
Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022.
code / bibtex / poster

We propose to learn representations of political actors with social context and expert knowledge, while applying learned representations in computational political science.

3DSP Heterogeneity-Aware Twitter Bot Detection with Relational Graph Transformers
Shangbin Feng, Zhaoxuan Tan, Rui Li, Minnan Luo
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022.
slides / code / bibtex

We propose the relational graph transformers GNN architecture to leverage the intrinsic relation heterogeneity and influence heterogeneity in Twitter network.

3DSP KALM: Knowledge-Aware Integration of Local, Document, and Global Contexts for Long Document Understanding
Shangbin Feng, Zhaoxuan Tan, Wenqian Zhang, Zhenyu Lei, Yulia Tsvetkov
arXiv preprint arXiv:2210.04105, 2022

We propose KALM, a Knowledge-Aware Language Model that jointly incorporates external local, document-level, and global context knowledge.

3DSP AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach
Shujie Yang, Binchi Zhang, Shangbin Feng, Zhaoxuan Tan, Qinghua Zheng, Ziqi Liu, Minnan Luo.
arXiv preprint arXiv:2208.08200, 2022.

We propose a graph anomaly detection framework based on triple attention named AHEAD to leverage heterogeneity in attributed networks.

Xi'an Jiaotong University
2019.08 - 2023.07 (Expected)

B.E. in Computer Science and Technology
GPA: 89.1 (+3) / 100.0 [top 6%]
Advisor: Prof. Minnan Luo
Academic Experiences
Tsvetshop @ University of Washington

Research Assistant         2022.10 - 2023.01
Developed a multi-dataset multi-model Twitter bot detection pipeline to probe what percentage of users on Twitter are bots.
Collaborator: Shangbin Feng, Melanie Sclar
Advisor: Prof. Yulia Tsvetkov
Virtual Collaboration @ National University of Singapore

Research Assistant         2022.08 - 2023.02
Working on a project that aims to understand the effect of anthropomorphic features on human-chatbot interaction.
Collaborator: Xin Huang, Zicheng Zhu
Advisor: Prof. Renwen Zhang
Knowledge Engineering Group (KEG) @ Tsinghua University

Research Assistant         2022.04 - 2022.11
Worked on kgTransformerv2: unifying reasoning tasks on large-scale knowledge graphs with pretraining-finetuning paradigm.
Won 4-th place in OGB@NeurIPS 2022 competition WikiKG90Mv2 track (CogDL-kgTransformer).
Mentor: Xiao Liu
Advisor: Prof. Yuxiao Dong
Luo lab Undergraduate Division (LUD) @ Xi'an Jiaotong University

Director         2022.06 - present
promoting undergraduate research by leading a 17-person undergraduate group, and mentoring 9 schoolmates alongside the other senior students.

Member         2021.08 - 2022.06
Conducted research on various topics including social network analysis, knowledge graph embedding, political actors representation learning, and heterogeneous graph anomaly detection.
Advisor: Prof. Minnan Luo

Luo lab Undergraduate Division (LUD)

Director         from 2022.06 to present
Official lab website

Lead a undergraduate reasearch group that promotes undergraduate research and bridges the gap between undergraduate studies and graduate research.
Honors & Awards
  • AAAI Student Scholarship, Association for the Advancement of Artificial Intelligence, 2022
  • National Second Prize, Contemporary Undergraduate Mathematical Contest in Modeling (CUMCM), China Society for Industrial and Applied Mathematics, 2021
  • Top Project Runner Up, NUS SoC Summer Workshop, 2021
  • Dean's List, Xi'an Jiaotong University, 2020, 2021, 2022
  • First Prize in Shaanxi Province, Contemporary Undergraduate Mathematical Contest in Modeling (CUMCM), China Society for Industrial and Applied Mathematics, 2020

  • I enjoy playing trumpet 🎺 and served as the principal trumpet player in my primary and high school band 🎼.
  • I am a big fan of Jules Verne, and especially fascinated with In Search of the Castaways, From the Earth to the Moon, and Five Weeks in a Balloon.
  • I also love jogging 🏃 and playing table tennis 🏓 in my free time 😄.

  • Template courtesy: Jon Barron.
    Last updated: Feb, 2023