Zijian Wang

I am currently a Tech Lead Manager at AWS AI Labs in the Amazon Q Developer team. We work on large language models (LLM) for code. Please feel free to email me for oppotunities in our team.

Previously, I was at Stanford and I was part of the Stanford NLP Group, advised by Prof. Chris Potts. Before that, I was at the University of Michigan, working with Prof. David Jurgens and Prof. Kevyn Collins-Thompson. Earlier, I studied at Shanghai Jiao Tong University.

I actively contribute to the community. I co-organize the LLM4Code workshop at ICSE'25 (submit here!) and previously co-organized the Deep Learning for Code (DL4C) workshop at ICLR'23. I serve as an Area Chair for ARR and regularly review for major ML conferences.

zijwang@cs.stanford.edu | Google Scholar | Linkedin | Follow @zijianwang30

Publications

*=equal contribution; ^†=author is an intern

	Learning Code Preference via Synthetic Evolution Jiawei Liu^†, Thanh Nguyen, Mingyue Shang, Hantian Ding, Xiaopeng Li, Yu Yu, Varun Kumar, and Zijian Wang arXiv, 2024 paper / summary
	Horizon-Length Prediction: Advancing Fill-in-the-Middle Capabilities for Code Generation with Lookahead Planning Yifeng Ding^†, Hantian Ding, Shiqi Wang, Qing Sun, Varun Kumar, and Zijian Wang arXiv, 2024 paper / summary
	Fewer Truncations Improve Language Modeling Hantian Ding, Zijian Wang, Giovanni Paolini, Varun Kumar, Anoop Deoras, Dan Roth, and Stefano Soatto ICML, 2024 paper / summary / Blogpost / 机器之心 (Blogpost in Chinese)
	CodeFort: Robust Training for Code Generation Models Yuhao Zhang^†, Shiqi Wang, Haifeng Qian, Zijian Wang, Mingyue Shang, Linbo Liu, Sanjay Krishna Gouda, Baishakhi Ray, Murali Krishna Ramanathan, Xiaofei Ma, and Anoop Deoras Findings of EMNLP, 2024 paper
	Token Alignment via Character Matching for Subword Completion Ben Athiwaratkun, Shiqi Wang, Mingyue Shang, Yuchen Tian, Zijian Wang, Sujan Kumar Gonugondla, Sanjay Krishna Gouda, Rob Kwiatowski, Ramesh Nallapati, and Bing Xiang Findings of ACL*, 2024 paper
	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 LREC-COLING*, 2024 paper
	CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion Yangruibo Ding^†, Zijian Wang, Wasi Ahmad, Hantian Ding, Ming Tan, Nihal Jain, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, and Bing Xiang NeurIPS (Datasets and Benchmarks Track)*, 2023 paper/webpage/data/code
	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 ACL, 2023 paper / code + data
	ContraCLM: 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 ACL*, 2023 paper
	A Static Evaluation of Code Completion by Large Language Models Hantian Ding, Varun Kumar, Yuchen Tian, Zijian Wang, Rob Kwiatkowski, Xiaopeng Li, Murali Krishna Ramanathan, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth and Bing Xiang ACL (Industry), 2023 paper
	Towards Greener Yet Powerful Code Generation via Quantization: An Empirical Study Xiaokai Wei, Sujan Gonugondla, Wasi Ahmad, Shiqi Wang, Baishakhi Ray, Haifeng Qian, Xiaopeng Li, Varun Kumar, Zijian Wang, Yuchen Tian, Qing Sun, Ben Athiwaratkun, Mingyue Shang, Murali Krishna Ramanathan, Parminder Bhatia, and Bing Xiang ESEC/FSE, 2023 paper
	Multi-lingual Evaluation of Code Generation Models Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, ...19 other authors..., Sudipta Sengupta, Dan Roth, and Bing Xiang ICLR, 2023 paper / code + data
	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
	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
	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
	NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation The NL-Augmenter Team arXiv, 2021 paper / code + data
	Modeling Subjective Assessments of Guilt in Newspaper Crime Narratives Elisa Kreiss, Zijian Wang, and Christopher Potts CoNLL, 2020 paper / code + data / video
	TalkDown: A Corpus for Condescension Detection in Context Zijian Wang and Christopher Potts EMNLP-IJCNLP, 2019 paper / code + data
	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
	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
	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
	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

Organizer/Program Committee/Reviewer:

Co-organizer of the second Deep Learning for Code (DL4C) workshop at ICLR'23
Area Chair of ARR
Outstanding Reviewer at ACL'21
Current or past reviewer of ICML, NeurIPS, ICLR, COLM, *ACL/ARR, ICWSM, WebSci, AAAI, IJCAI, and many workshops

Teaching Assistant:

CS 224U Natural Language Understanding, Spring 2020, Stanford University
Applied Machine Learning (Coursera MOOC by the University of Michigan), 2017-2018, University of Michigan (founding and head TA, 250k+ enrollment)
Introduction to Programming, Summer 2015, Shanghai Jiao Tong University
Academic Writing II, Spring 2015, Shanghai Jiao Tong University
Academic Writing I, Fall 2014, Shanghai Jiao Tong University

Other:

Volunteer: EMNLP 19
Webmaster: Stanford NLP Group (2019-2020)
Transfer Student Leader: University of Michigan (2017-2018)

Homepage credits: Jon Barron