Boxin Wang

Ph.D. student
Computer Science
University of Illinois at Urbana-Champaign

Contact: boxinw2@illinois.edu
[Google Scholar] [GitHub] [Linkedln]

I am a fourth year Computer Science Ph.D. candidate at University of Illinois, Urbana-Champaign (UIUC). I work as a research assistant in Secure Learning Lab supervised by Prof. Bo Li.

My research interests are trustworthy machine learning (ML) and natural language processing (NLP). My research vision is to develop practical and scalable language models (LMs), and close the trustworthiness gap, focusing on three interconnected pillars of trustworthy NLP: robustness, privacy, and ethics.

News

[2023/10] One paper got accepted to EMNLP 2023 main conference!
[2023/09] One paper got accepted to NeurIPS 2023 as oral presentations!
[2023/05] I started my internship at NVIDIA. Look forward to seeing you in the Bay Area!
[2023/05] I am organizing Trustworthy and Reliable Large-Scale Machine Learning Models workshop at ICLR 2023.
[2022/10] I feel so honored to receive the NeurIPS 2022 Scholar Award!
[2022/09] Two papers got accepted to NeurIPS 2022.
[2022/05] I am excited to join Google Research in summer as a research intern. Look forward to seeing you in the Bay Area!
[2022/05] One paper got accepted to Findings of NAACL 2022.
[2021/11] I passed the qualifying exam and officially became a Ph.D. candidate 🎉.
[2021/10] Two papers got accepted to NeurIPS 2021.
[2021/10] One paper got accepted to EMNLP 2021.
[2021/6] I am excited to join NVIDIA in summer as a research intern.
[2021/5] One paper got accepted to ICML 2021.
[2021/5] One paper got accepted to ACM CCS 2021.
[2021/3] I am so honored to receive the Yunni & Maxine Pao Memorial Fellowship for 2021-2022 academic year.

Publications

2023

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models NeurIPS 2023 (Oral)

Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li. [PDF][website][code]

Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study EMNLP 2023

Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro [PDF][code]

Can Public Large Language Models Help Private Cross-device Federated Learning? ICML ES-Fomo Workshop 2023

Boxin Wang, Yibo Jacky Zhang, Yuan Cao, Bo Li, H. Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer [PDF]

2022

Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models NeurIPS 2022

Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro [PDF][code]

Improving Certified Robustness via Statistical Learning with Logical Reasoning NeurIPS 2022

Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlaš, Ji Liu, Heng Guo, Ce Zhang, Bo Li [PDF]

SemAttack: Natural Textual Attacks via Different Semantic Spaces NAACL 2022 (Findings)

Boxin Wang*, Chejian Xu*, Xiangyu Liu, Yu Cheng, Bo Li [PDF] [Code]

Certifying Out-of-Domain Generalization for Blackbox Functions ICML 2022

Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang [PDF]

2021

Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models NeurIPS 2021 (Oral)

Boxin Wang*, Chejian Xu*, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, Bo Li [PDF] [Dataset]

G-PATE: Scalable Differentially Private Data Generator via Private Aggregation
of Teacher Discriminators NeurIPS 2021

Yunhui Long*, Boxin Wang*, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li [PDF] [Code]

DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation CCS 2021

Boxin Wang*, Fan Wu*, Yunhui Long*, Luka Rimanic, Ce Zhang, Bo Li [PDF] [Code]

Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability ICML 2021

Kaizhao Liang*, Jacky Zhang*, Boxin Wang, Zhuolin Yang, Sanmi Koyejo, Bo Li [PDF] [Code]

Counterfactual Adversarial Learning with Representation Interpolation EMNLP 2021

Wei Wang, Boxin Wang, Ning Shi, Jinfeng Li, Bingyu Zhu, Xiangyu Liu, Rong Zhang [PDF] [Code]

Incorporating External POS Tagger for Punctuation Restoration Interspeech 2021

Ning Shi, Wei Wang, Boxin Wang, Jinfeng Li, Xiangyu Liu, Zhouhan Lin [PDF][Code]

InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective ICLR 2021

Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu [PDF][Code]

2020

T3: Tree-Autoencoder Regularized Adversarial Text Generation for Targeted Attack EMNLP 2020

Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang and Bo Li [PDF][Code]

Reinforcement-Learning based Portfolio Management with Augmented Asset Movement
Prediction States AAAI 2020

Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Jun Xiao, Bo Li [PDF]

2019

Efficient task-specific data valuation for nearest neighbor algorithms PVLDB 2019

Ruoxi Jia*, David Dao*, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song [PDF]

Towards efficient data valuation based on the shapley value AISTATS 2019

Ruoxi Jia*, David Dao*, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos [PDF]

Experiences

[2022/10-Present] NVIDIA Research
- Research Intern, advised by Dr. Wei Ping, Dr. Mohammad Shoeybi, Prof. Chaowei Xiao and Prof. Anima Anandkumar
[2022/05-2022/08] Google Research
- Research Intern, advised by Dr. Zheng Xu, Dr. Yuan Cao, and Dr. Manzil Zaheer
[2021/06-2022/05] NVIDIA Research
- Research Intern, advised by Dr. Wei Ping, Dr. Mohammad Shoeybi, Prof. Chaowei Xiao and Prof. Anima Anandkumar
[2021/01-2021/05] Alibaba Group
- Research Intern, in AI Security Team
[2020/05-2020/12] Microsoft Research, Redmond
- Research Intern, advised by Dr. Shuohang Wang, Dr. Zhe Gan and Dr. Yu Cheng
[2019/07-2019/08] Wechat Group, Tencent
- Research Intern, advised by Prof. Bo Li and Qian Chen
[2018/05-2018/08] Alibaba Group
- Software Engineer Intern, in Distributed Relational Database Team

Personal

I like photographing. I put my photos on 500px.