Zijian Wang

I am currently an Applied Scientist at AWS AI Labs, working on large-scale language model pretraining and its application to code.

I graduated with a research-based master's degree in Symbolic Systems from Stanford University in 2020. My research focuses on Natural Language Processing, with an emphasis on Computational Social Science, Computational Pragmatics, and Question Answering. I was a member of the Stanford NLP Group, advised by Prof. Chris Potts.

Previously, I received my Bachelor's degree in Computer Science and Linguistics from the University of Michigan, where I worked with Prof. David Jurgens and Prof. Kevyn Collins-Thompson. I received a second/dual Bachelor's degree in Electrical and Computer Engineering from Shanghai Jiao Tong University via the dual degree program.

Email: zijwang@cs.stanford.edu  |  Twitter  |  Google Scholar  |  CV       

2023/01: I am co-organizing the second Deep Learning for Code (DL4C) workshop at ICLR'23. The deadline is Feb. 3rd, 2023. Please consider submitting your work to our workshop :)

profile photo
Publications

*=equal contribution; =author is an intern

ding2022cocomic CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context
Yangruibo Ding*, Zijian Wang*, Wasi Ahmad*, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, and Bing Xiang
arXiv, 2022
paper
wang2022recode ReCode: Robustness Evaluation of Code Generation Models
Shiqi Wang*, Zheng Li*, Haifeng Qian, Chenghao Yang, Zijian Wang, Mingyue Shang, Varun Kumar, Samson Tan, Baishakhi Ray, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Dan Roth, and Bing Xiang
arXiv, 2022
paper / code + data
ben2022mbxp Multi-lingual Evaluation of Code Generation Models
Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Ahmad Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, and Bing Xiang
ICLR, 2023
paper / code + data
jain2022contragen ContraGen: Effective Contrastive Learning For Causal Language Model
Nihal Jain*, Dejiao Zhang*, Wasi Ahmad*, Zijian Wang, Feng Nan, Xiaopeng Li, Ming Tan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Xiaofei Ma, and Bing Xiang
arXiv, 2022
paper
li2022debiasing Debiasing Neural Retrieval via In-batch Balancing Regularization
Yuantong Li, Xiaokai Wei*, Zijian Wang*, Shen Wang*, Xiaofei Ma, Parminder Bhatia, and Andrew Arnold
4th Workshop on Gender Bias in Natural Language Processing at NAACL, 2022
paper
bombari2022towards Towards Differential Relational Privacy and its use in Question Answering
Simone Bombari, Alessandro Achille, Zijian Wang, Yu-Xiang Wang, Yusheng Xie, Kunwar Yashraj Singh, Srikar Appalaraju, Vijay Mahadevan, and Stefano Soatto
arXiv, 2022
paper
li2022dqbart DQ-BART: Efficient Sequence-to-Sequence Model via Joint Distillation and Quantization
Zheng Li*, Zijian Wang*, Ming Tan, Ramesh Nallapati, Parminder Bhatia, Andrew Arnold, Bing Xiang, and Dan Roth
ACL, 2022
paper / code
dhole2021nl NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
The NL-Augmenter Team
arXiv, 2021
paper / code + data
kreiss2020modeling Modeling Subjective Assessments of Guilt in Newspaper Crime Narratives
Elisa Kreiss*, Zijian Wang*, and Christopher Potts
CoNLL, 2020
paper / code + data / video
wang2019talkdown TalkDown: A Corpus for Condescension Detection in Context
Zijian Wang and Christopher Potts
EMNLP-IJCNLP, 2019
paper / code + data
qi2019answering Answering Complex Open-Domain Questions Through Iterative Query Generation
Peng Qi, Xianwen Lin*, Leo Mehr*, Zijian Wang*, and Christopher D. Manning
EMNLP-IJCNLP, 2019
paper / code / blog post
wang2019demographic Demographic Inference and Representative Population Estimates from \ Social Media Data (Best Poster Award)
Zijian Wang, Scott A. Hale, David Adelani, Przemyslaw A. Grabowicz, Timo Hartmann, Fabian Flöck, and David Jurgens
TheWebConf (WWW), 2019 (also presented at IC2S2 2019)
paper / demo / code / pip-installable package / poster
wang2018its It's going to be okay: Measuring Access to Support in Online Communities
Zijian Wang and David Jurgens
EMNLP, 2018
paper / project webpage / pip-installable package
choi2017social Social work in the classroom? A tool to evaluate topical relevance in student writing
Heeryung Choi, Zijian Wang, Christopher Brooks, Kevyn Collins-Thompson, Beth Glover Reed, and Dale Fitch
EDM, 2017
paper
Academic Services

Teaching Assistant:

Organizer/Program Committee/Reviewer:

  • Co-organizer of the second Deep Learning for Code (DL4C) workshop at ICLR'23
  • ACL, EMNLP, NAACL, ARR, ICML, NeurIPS, ICWSM, WebSci, AAAI, IJCAI, and their workshops 19'-22'
  • Outstanding Reviewer at ACL'21

Other:

  • Volunteer: EMNLP 19
  • Webmaster: Stanford NLP Group (2019-2020)
  • Admission Reader: Stanford Symbolic Systems Program (2019 & 2020)
  • Transfer Student Leader: University of Michigan (2017-2018)


Homepage credits: Jon Barron