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2020 – today
- 2025
[i25]Alisson G. Azzolini, Hannah Brandon, Prithvijit Chattopadhyay, Huayu Chen, Jinju Chu, Yin Cui, Jenna Diamond, Yifan Ding, Francesco Ferroni, Rama Govindaraju, Jinwei Gu, Siddharth Gururani, Imad El Hanafi, Zekun Hao, Jacob Samuel Huffman, Jingyi Jin, Brendan Johnson, Rizwan Khan, George Kurian, Elena Lantz, Nayeon Lee, Zhaoshuo Li, Xuan Li, Tsung-Yi Lin, Yen-Chen Lin, Ming-Yu Liu, Alice Luo, Andrew Mathau, Yun Ni, Lindsey Pavao, Wei Ping, David W. Romero, Misha Smelyanskiy, Shuran Song, Lyne Tchapmi, Andrew Z. Wang, Boxin Wang, Haoxiang Wang, Fangyin Wei, Jiashu Xu, Yao Xu, Xiaodong Yang, Zhuolin Yang, Xiaohui Zeng, Zhe Zhang:
Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning. CoRR abs/2503.15558 (2025)- [i24]Aaron Blakeman, Aarti Basant, Abhinav Khattar, Adithya Renduchintala, Akhiad Bercovich, Aleksander Ficek, Alexis Bjorlin, Ali Taghibakhshi, Amala Sanjay Deshmukh, Ameya Sunil Mahabaleshwarkar, Andrew Tao, Anna Shors, Ashwath Aithal, Ashwin Poojary, Ayush Dattagupta, Balaram Buddharaju, Bobby Chen, Boris Ginsburg, Boxin Wang, Brandon Norick, Brian Butterfield, Bryan Catanzaro, Carlo del Mundo, Chengyu Dong, Christine Harvey, Christopher Parisien, Dan Su, Daniel Korzekwa, Danny Yin, Daria Gitman, David Mosallanezhad, Deepak Narayanan, Denys Fridman, Dima Rekesh, Ding Ma, Dmytro Pykhtar, Dong Ahn, Duncan Riach, Dusan Stosic, Eileen Long, Elad Segal, Ellie Evans, Eric Chung, Erick Galinkin, Evelina Bakhturina, Ewa Dobrowolska, Fei Jia, Fuxiao Liu, Gargi Prasad, Gerald Shen, Guilin Liu, Guo Chen, Haifeng Qian, Helen Ngo, Hongbin Liu, Hui Li, Igor Gitman, Ilia Karmanov, Ivan Moshkov, Izik Golan, Jan Kautz, Jane Polak Scowcroft, Jared Casper, Jarno Seppänen, Jason Lu, Jason Sewall, Jiaqi Zeng, Jiaxuan You, Jimmy Zhang, Jing Zhang, Jining Huang, Jinze Xue, Jocelyn Huang, Joey Conway, John Kamalu, Jon Barker, Jonathan M. Cohen, Joseph Jennings, Jupinder Parmar, Karan Sapra, Kari Briski, Kateryna Chumachenko, Katherine Luna, Keshav Santhanam, Kezhi Kong, Kirthi Sivamani, Krzysztof Pawelec, Kumar Anik, Kunlun Li, Lawrence McAfee, Leon Derczynski, Lindsey Pavao, Luis Vega, Lukas Voegtle, Maciej Bala, Maer Rodrigues de Melo, Makesh Narsimhan Sreedhar, Marcin Chochowski, Markus Kliegl:
Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models. CoRR abs/2504.03624 (2025) - [i23]Chejian Xu, Wei Ping, Peng Xu, Zihan Liu, Boxin Wang, Mohammad Shoeybi, Bo Li, Bryan Catanzaro:
From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models. CoRR abs/2504.06214 (2025) - 2024
- [c22]Fengqing Jiang
, Zhangchen Xu, Luyao Niu, Boxin Wang, Jinyuan Jia, Bo Li, Radha Poovendran:
POSTER: Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications. AsiaCCS 2024 - [c21]Yuanhao Xiong, Yixin Nie, Haotian Liu, Boxin Wang, Jun Chen, Rong Jin, Cho-Jui Hsieh, Lorenzo Torresani, Jie Lei:
UNICORN: A Unified Causal Video-Oriented Language-Modeling Framework for Temporal Video-Language Tasks. EMNLP 2024: 12983-12997 - [c20]Boxin Wang, Wei Ping, Lawrence McAfee, Peng Xu, Bo Li, Mohammad Shoeybi, Bryan Catanzaro:
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining. ICML 2024 - [c19]Boxin Wang, Yibo Zhang, Yuan Cao, Bo Li, Hugh McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer:
Can Public Large Language Models Help Private Cross-device Federated Learning? NAACL-HLT (Findings) 2024: 934-949 - [c18]Yue Yu, Wei Ping, Zihan Liu, Boxin Wang, Jiaxuan You, Chao Zhang, Mohammad Shoeybi, Bryan Catanzaro:
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs. NeurIPS 2024 - [i22]Yue Yu, Wei Ping, Zihan Liu, Boxin Wang, Jiaxuan You, Chao Zhang, Mohammad Shoeybi, Bryan Catanzaro:
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs. CoRR abs/2407.02485 (2024) - [i21]Wenliang Dai, Nayeon Lee, Boxin Wang, Zhuoling Yang, Zihan Liu, Jon Barker, Tuomas Rintamaki, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping:
NVLM: Open Frontier-Class Multimodal LLMs. CoRR abs/2409.11402 (2024) - 2023
- [c17]Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro:
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study. EMNLP 2023: 7763-7786 - [c16]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:
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. NeurIPS 2023 - [i20]Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro:
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study. CoRR abs/2304.06762 (2023) - [i19]Boxin Wang, Jacky Yibo Zhang, Yuan Cao, Bo Li, H. Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer:
Can Public Large Language Models Help Private Cross-device Federated Learning? CoRR abs/2305.12132 (2023) - [i18]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:
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. CoRR abs/2306.11698 (2023) - [i17]Boxin Wang, Wei Ping, Lawrence McAfee, Peng Xu, Bo Li, Mohammad Shoeybi, Bryan Catanzaro:
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining. CoRR abs/2310.07713 (2023) - [i16]Fengqing Jiang, Zhangchen Xu, Luyao Niu, Boxin Wang, Jinyuan Jia, Bo Li, Radha Poovendran:
Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications. CoRR abs/2311.16153 (2023) - 2022
- [c15]Ning Shi, Boxin Wang, Wei Wang, Xiangyu Liu, Zhouhan Lin:
Revisit Systematic Generalization via Meaningful Learning. BlackboxNLP@EMNLP 2022: 62-79 - [c14]Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang:
Certifying Out-of-Domain Generalization for Blackbox Functions. ICML 2022: 23527-23548 - [c13]Boxin Wang, Chejian Xu, Xiangyu Liu, Yu Cheng, Bo Li:
SemAttack: Natural Textual Attacks via Different Semantic Spaces. NAACL-HLT (Findings) 2022: 176-205 - [c12]Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro:
Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models. NeurIPS 2022 - [c11]Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlas, Ji Liu, Heng Guo, Ce Zhang, Bo Li:
Improving Certified Robustness via Statistical Learning with Logical Reasoning. NeurIPS 2022 - [i15]Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang:
Certifying Out-of-Domain Generalization for Blackbox Functions. CoRR abs/2202.01679 (2022) - [i14]Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro:
Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models. CoRR abs/2202.04173 (2022) - [i13]Boxin Wang, Chejian Xu, Xiangyu Liu, Yu Cheng, Bo Li:
SemAttack: Natural Textual Attacks via Different Semantic Spaces. CoRR abs/2205.01287 (2022) - [i12]Wenda Chu, Chulin Xie, Boxin Wang, Linyi Li, Lang Yin, Han Zhao, Bo Li:
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data. CoRR abs/2207.10265 (2022) - 2021
- [c10]Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li:
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CCS 2021: 2146-2168 - [c9]Wei Wang, Boxin Wang, Ning Shi, Jinfeng Li, Bingyu Zhu, Xiangyu Liu, Rong Zhang:
Counterfactual Adversarial Learning with Representation Interpolation. EMNLP (Findings) 2021: 4809-4820 - [c8]Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu:
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective. ICLR 2021 - [c7]Kaizhao Liang, Jacky Y. Zhang, Boxin Wang, Zhuolin Yang, Sanmi Koyejo, Bo Li:
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability. ICML 2021: 6577-6587 - [c6]Ning Shi, Wei Wang, Boxin Wang, Jinfeng Li, Xiangyu Liu, Zhouhan Lin:
Incorporating External POS Tagger for Punctuation Restoration. Interspeech 2021: 1987-1991 - [c5]Yunhui Long, Boxin Wang, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li:
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators. NeurIPS 2021: 2965-2977 - [c4]Boxin Wang, Chejian Xu, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, Bo Li:
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models. NeurIPS Datasets and Benchmarks 2021 - [i11]Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li:
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CoRR abs/2103.11109 (2021) - [i10]Ning Shi, Wei Wang, Boxin Wang, Jinfeng Li, Xiangyu Liu, Zhouhan Lin:
Incorporating External POS Tagger for Punctuation Restoration. CoRR abs/2106.06731 (2021) - [i9]Wei Wang, Boxin Wang, Ning Shi, Jinfeng Li, Bingyu Zhu, Xiangyu Liu, Rong Zhang:
Counterfactual Adversarial Learning with Representation Interpolation. CoRR abs/2109.04746 (2021) - [i8]Boxin Wang, Chejian Xu, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, Bo Li:
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models. CoRR abs/2111.02840 (2021) - 2020
- [c3]Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Ju Xiao, Bo Li:
Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States. AAAI 2020: 1112-1119 - [c2]Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang, Bo Li:
T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack. EMNLP (1) 2020: 6134-6150 - [i7]Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Jun Xiao, Bo Li:
Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States. CoRR abs/2002.05780 (2020) - [i6]Zhuolin Yang, Zhikuan Zhao, Hengzhi Pei, Boxin Wang, Bojan Karlas, Ji Liu, Heng Guo, Bo Li, Ce Zhang:
End-to-end Robustness for Sensing-Reasoning Machine Learning Pipelines. CoRR abs/2003.00120 (2020) - [i5]Boxin Wang, Boyuan Pan, Xin Li, Bo Li:
Towards Evaluating the Robustness of Chinese BERT Classifiers. CoRR abs/2004.03742 (2020) - [i4]Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu:
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective. CoRR abs/2010.02329 (2020)
2010 – 2019
- 2019
- [j1]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song:
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. Proc. VLDB Endow. 12(11): 1610-1623 (2019) - [c1]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos:
Towards Efficient Data Valuation Based on the Shapley Value. AISTATS 2019: 1167-1176 - [i3]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos:
Towards Efficient Data Valuation Based on the Shapley Value. CoRR abs/1902.10275 (2019) - [i2]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song:
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. CoRR abs/1908.08619 (2019) - [i1]Boxin Wang, Hengzhi Pei, Han Liu, Bo Li:
AdvCodec: Towards A Unified Framework for Adversarial Text Generation. CoRR abs/1912.10375 (2019)
Coauthor Index
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