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ORCIDAlexander Bukharin
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2020 – today
- 2025
[c8]Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong:
HelpSteer2-Preference: Complementing Ratings with Preferences. ICLR 2025- [i16]Shengyang Sun, Yian Zhang, Alexander Bukharin, David Mosallanezhad, Jiaqi Zeng, Soumye Singhal, Gerald Shen, Adithya Renduchintala, Tugrul Konuk, Yi Dong, Zhilin Wang, Dmitry Chichkov, Olivier Delalleau, Oleksii Kuchaiev:
Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment. CoRR abs/2502.00203 (2025) - [i15]Alexander Bukharin, Haifeng Qian, Shengyang Sun, Adithya Renduchintala, Soumye Singhal, Zhilin Wang, Oleksii Kuchaiev, Olivier Delalleau, Tuo Zhao:
Adversarial Training of Reward Models. CoRR abs/2504.06141 (2025) - [i14]Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Hoo-Chang Shin, Felipe Soares, Alexander Bukharin, Ellie Evans, Yi Dong, Oleksii Kuchaiev:
HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages. CoRR abs/2505.11475 (2025) - [i13]Mingjie Liu, Shizhe Diao, Jian Hu, Ximing Lu, Xin Dong, Hao Zhang, Alexander Bukharin, Shaokun Zhang, Jiaqi Zeng, Makesh Narsimhan Sreedhar, Gerald Shen, David Mosallanezhad, Di Zhang, Jonas Yang, June Yang, Oleksii Kuchaiev, Guilin Liu, Zhiding Yu, Pavlo Molchanov, Yejin Choi, Jan Kautz, Yi Dong:
Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training. CoRR abs/2507.12507 (2025) - [i12]Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, Abhinav Khattar, Adithya Renduchintala, Aditya Malte, Akhiad Bercovich, Akshay Hazare, Alejandra Rico, Aleksander Ficek, Alex Kondratenko, Alex Shaposhnikov, Alexander Bukharin, Ali Taghibakhshi, Amelia Barton, Ameya Sunil Mahabaleshwarkar, Amy Shen, Andrew Tao, Ann Guan, Anna Shors, Anubhav Mandarwal, Arham Mehta, Arun Venkatesan, Ashton Sharabiani, Ashwath Aithal, Ashwin Poojary, Ayush Dattagupta, Balaram Buddharaju, Banghua Zhu, Barnaby Simkin, Bilal Kartal, Bita Darvish Rouhani, Bobby Chen, Boris Ginsburg, Brandon Norick, Brian Yu, Bryan Catanzaro, Charles Wang, Charlie Truong, Chetan Mungekar, Chintan Patel, Chris Alexiuk, Christian Munley, Christopher Parisien, Dan Su, Daniel Afrimi, Daniel Korzekwa, Daniel Rohrer, Daria Gitman, David Mosallanezhad, Deepak Narayanan, Dima Rekesh, Dina Yared, Dmytro Pykhtar, Dong Ahn, Duncan Riach, Eileen Long, Elliott Ning, Eric Chung, Erick Galinkin, Evelina Bakhturina, Gargi Prasad, Gerald Shen, Haifeng Qian, Haim Elisha, Harsh Sharma, Hayley Ross, Helen Ngo, Herman Sahota, Hexin Wang, Hoo Chang Shin, Hua Huang, Iain Cunningham, Igor Gitman, Ivan Moshkov, Jaehun Jung, Jan Kautz, Jane Polak Scowcroft, Jared Casper, Jian Zhang, Jiaqi Zeng, Jimmy Zhang, Jinze Xue, Jocelyn Huang, Joey Conway, John Kamalu, Jonathan M. Cohen, Joseph Jennings, Julien Veron Vialard, Junkeun Yi, Jupinder Parmar, Kari Briski, Katherine Cheung, Katherine Luna, Keith W. Ross, Keshav Santhanam, Kezhi Kong, Krzysztof Pawelec, Kumar Anik:
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model. CoRR abs/2508.14444 (2025) - 2024
- [c7]Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, Haoming Jiang:
Data Diversity Matters for Robust Instruction Tuning. EMNLP (Findings) 2024: 3411-3425 - [c6]Alexander Bukharin, Ilgee Hong, Haoming Jiang, Zichong Li, Qingru Zhang, Zixuan Zhang, Tuo Zhao:
Robust Reinforcement Learning from Corrupted Human Feedback. NeurIPS 2024 - [c5]Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao:
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. NeurIPS 2024 - [i11]Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao:
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. CoRR abs/2406.02764 (2024) - [i10]Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao:
Robust Reinforcement Learning from Corrupted Human Feedback. CoRR abs/2406.15568 (2024) - [i9]Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li:
RNR: Teaching Large Language Models to Follow Roles and Rules. CoRR abs/2409.13733 (2024) - [i8]Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong:
HelpSteer2-Preference: Complementing Ratings with Preferences. CoRR abs/2410.01257 (2024) - 2023
- [c4]Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao:
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. ICLR 2023 - [c3]Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao:
Machine Learning Force Fields with Data Cost Aware Training. ICML 2023: 3219-3232 - [c2]Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao:
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. NeurIPS 2023 - [i7]Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao:
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. CoRR abs/2303.10512 (2023) - [i6]Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao:
Machine Learning Force Fields with Data Cost Aware Training. CoRR abs/2306.03109 (2023) - [i5]Alexander Bukharin, Yixiao Li, Pengcheng He, Weizhu Chen, Tuo Zhao:
Deep Reinforcement Learning from Hierarchical Weak Preference Feedback. CoRR abs/2309.02632 (2023) - [i4]Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao:
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. CoRR abs/2310.10810 (2023) - [i3]Alexander Bukharin, Tuo Zhao:
Data Diversity Matters for Robust Instruction Tuning. CoRR abs/2311.14736 (2023) - 2022
- [j2]Shixiang Zhu
, Alexander Bukharin, Liyan Xie, Khurram Yamin, Shihao Yang, Pinar Keskinocak, Yao Xie:
Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data. IEEE J. Sel. Top. Signal Process. 16(2): 250-260 (2022) - [c1]Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao:
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. ICML 2022: 26809-26823 - [i2]Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao:
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. CoRR abs/2206.12562 (2022) - 2021
- [j1]Shixiang Zhu, Alexander Bukharin, Liyan Xie, Mauricio Santillana, Shihao Yang, Yao Xie:
High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S. ACM Trans. Manag. Inf. Syst. 12(4): 33:1-33:20 (2021) - [i1]Shixiang Zhu, Alexander Bukharin, Liyan Xie, Shihao Yang, Pinar Keskinocak, Yao Xie:
Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data. CoRR abs/2106.00072 (2021)
Coauthor Index
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