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Clustering Document Parts: Detecting and Characterizing Influence Campaigns from Documents
Zhengxiang Xiang, Owen Rambow,
the 6th workshop on NLP+CSS at NAACL 2024
王政祥
Commonly known as Jack Wang
“因真理,得自由,以服务。”
"Freedom through Truth for Service."
I am a PhD student in Computational Linguistics at Stony Brook University (since Fall 2022) and a member of the Institute for Advanced Computational Science (IACS). My advisors are Dr. Owen Rambow and Dr. Jeffrey Heinz.
Over years, I have worked on projects that study actual language use at large scale, data augmentation, text clustering, as well as how and how well neural networks learn and generalize. I am currently working on the evaluation of Large Language Models (LLMs). I consider myself as a life-time learner.
News: I am a Data Scientist Intern at the Home Depot over this summer.
Availabilities: I am currently in the job market for a ML/NLP/Data Science internship (research or engineering) for 2024 Fall (part-time), 2024 Winter/Spring (part-time), and 2025 Summer (full-time). Free feel to reach out if you find my background interesting and relevant!
I was born and raised in Fuqing, a small southeastern town of China. Prior to coming to Stony Brook, I completed a bachelor's degree in Chinese Language and Literature from Hunan University, and a master's degree in Applied linguistics from University of Saskatchewan.
I am a proud self-taught and self-motivated programmer. I started learning programming in 2020, and have since managed to make programming relevant to and then part of my daily life. Looking back, I am glad to find my experiences with NLP align well with the three major phases of the field featured as: rule-based (symbolic) methods, statistical machine learning, and deep learning. I also find myself fortuante to witness the rapid development of the field over the past few years.
While I am not doing research, I enjoy reading random stuffs and exploring new places.
Here is my Curriculum Vitae.
For a full and up-to-date list of publications, please check my Google Scholar page.
Clustering Document Parts: Detecting and Characterizing Influence Campaigns from Documents
Zhengxiang Xiang, Owen Rambow,
the 6th workshop on NLP+CSS at NAACL 2024
Learning Transductions and Alignments with RNN Seq2seq models
Zhengxiang Xiang, ICGI 2023
 
Developing literature review writing skills through an online writing tutorial series: Corpus-based evidence
Zhi Li, Makarova Veronika, Zhengxiang Wang, Frontiers in Communication, 2023
Random Text Perturbations Work, but not Always
Zhengxiang Wang, AACL-IJCNLP 2022 Workshop Eval4NLP
Thirty-Two Years of IEEE VIS: Authors, Fields of Study and Citations
Hongtao Hao,
Yumian Cui,
Zhengxiang Wang,
Yea-Seul Kim,
IEEE Transactions on Visualization and Computer Graphics, 2022
 
Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chinese Question Matching
Zhengxiang Wang, ICNLSP 2022
 
A macroscopic re-examination of language and gender: a corpus-based case study in the university classroom setting
Zhengxiang Wang, MA thesis, University of Saskatchewan [Slides], 2021