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Boxin Wang - Homepage
Boxin Wang
Senior Research Scientist
NVIDIA
Contact: boxinw@nvidia.com
[Google Scholar]
[GitHub]
[Linkedln]
I am a Senior Research Scientist at NVIDIA.
I obtained my Ph.D. degree from the Computer Science department of University of Illinois, Urbana-Champaign (UIUC).
During my Ph.D., I was supervised by Prof. Bo Li.
My research vision is to develop practical and scalable large language models (LLMs) and close the trustworthiness gap. My research interests lie in but not limited to:
- Trustworthiness, alignment, and reasoning
- Multi-modal language modeling
- Retrieval-augmented generation (RAG)
News
- [2025/04] Our work Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models is out! Honored to be part of the core contributors to build VLM for Nemotron-H
- [2024/03] Our work Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning is out! Honored to be part of the core contributors for base VLM training of Cosmos-Reason1
- [2024/09] Our work NVLM: Open Frontier-Class Multimodal LLMs is out! Feel free to reach out to me if you are interested in our work 🎉
- [2024/09] Our work DecodingTrust is awarded the winner of Cybersecurity Award in the track of "Best Machine Learning and Security Paper" 🎉
- [2023/12] Our work DecodingTrust is awarded NeurIPS 2023 outstanding paper. 🎉
- [2023/10] I passed my Ph.D. defense! 🎉
- [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.
Publications
2025
From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models
2025
Chejian Xu, Wei Ping, Peng Xu, Zihan Liu, Boxin Wang, Mohammad Shoeybi, Bo Li, Bryan Catanzaro
[PDF][Models]
2024
RankRAG: Unifying Retrieval-Augmented Generation and Context Ranking in LLMs
NeurIPS 2024
Yue Yu, Wei Ping, Zihan Liu, Boxin Wang, Jiaxuan You, Chao Zhang, Mohammad Shoeybi, Bryan Catanzaro
[PDF]
Can Public Large Language Models Help Private Cross-device Federated Learning?
NAACL 2024 (Findings)
Boxin Wang, Yibo Jacky Zhang, Yuan Cao, Bo Li, H. Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer
[PDF]
UNICORN: A Unified Causal Video-Oriented Language-Modeling Framework for Temporal Video-Language Tasks
EMNLP 2024
Yuanhao Xiong, Yixin Nie, Haotian Liu, Boxin Wang, Jun Chen, Rong Jin, Cho-Jui Hsieh, Lorenzo Torresani, Jie Lei
[PDF]
2023
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
NeurIPS 2023 (Outstanding Paper)
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]
2022
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]
Certifying Out-of-Domain Generalization for Blackbox Functions
ICML 2022
Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang
[PDF]
2021
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]
Prediction States AAAI 2020
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]
Personal
I like photographing. I put my photos on 500px.