Alexander Bukharin

27 papers A* 8Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation. CoRR Zhuolin Yang, Zihan Liu, Yang Chen, Wenliang Dai, Boxin Wang, Sheng-Chieh Lin, Chankyu Lee, Yangyi Chen, Dongfu Jiang, Jiafan He, Renjie Pi, Grace Lam, Nayeon Lee, Alexander Bukharin, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping
2025	J	`jnl`	Adversarial Training of Reward Models. CoRR Alexander Bukharin, Haifeng Qian, Shengyang Sun, Adithya Renduchintala, Soumye Singhal, Zhilin Wang, Oleksii Kuchaiev, Olivier Delalleau, Tuo Zhao
2025	A*	`conf`	Deep Reinforcement Learning from Hierarchical Preference Design. ICML Alexander Bukharin, Yixiao Li, Pengcheng He, Tuo Zhao
2025	A*	`conf`	HelpSteer2-Preference: Complementing Ratings with Preferences. ICLR Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong
2025	J	`jnl`	HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages. CoRR Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Hoo-Chang Shin, Felipe Soares, Alexander Bukharin, Ellie Evans, Yi Dong, Oleksii Kuchaiev
2025	J	`jnl`	Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment. CoRR 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
2025	J	`jnl`	Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training. CoRR 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
2024	A*	`conf`	Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. NeurIPS Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao
2024	J	`jnl`	Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. CoRR Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao
2024	—	`conf`	Data Diversity Matters for Robust Instruction Tuning. EMNLP (Findings) Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, Haoming Jiang
2024	J	`jnl`	HelpSteer2-Preference: Complementing Ratings with Preferences. CoRR Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong
2024	J	`jnl`	RNR: Teaching Large Language Models to Follow Roles and Rules. CoRR Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li
2024	A*	`conf`	Robust Reinforcement Learning from Corrupted Human Feedback. NeurIPS Alexander Bukharin, Ilgee Hong, Haoming Jiang, Zichong Li, Qingru Zhang, Zixuan Zhang, Tuo Zhao
2024	J	`jnl`	Robust Reinforcement Learning from Corrupted Human Feedback. CoRR Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao
2023	A*	`conf`	Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. ICLR Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
2023	J	`jnl`	Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. CoRR Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
2023	J	`jnl`	Data Diversity Matters for Robust Instruction Tuning. CoRR Alexander Bukharin, Tuo Zhao
2023	J	`jnl`	Deep Reinforcement Learning from Hierarchical Weak Preference Feedback. CoRR Alexander Bukharin, Yixiao Li, Pengcheng He, Weizhu Chen, Tuo Zhao
2023	A*	`conf`	Machine Learning Force Fields with Data Cost Aware Training. ICML Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao
2023	J	`jnl`	Machine Learning Force Fields with Data Cost Aware Training. CoRR Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao
2023	A*	`conf`	Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. NeurIPS Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
2023	J	`jnl`	Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. CoRR Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
2022	J	`jnl`	Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data. IEEE J. Sel. Top. Signal Process. Shixiang Zhu, Alexander Bukharin, Liyan Xie, Khurram Yamin, Shihao Yang, Pinar Keskinocak, Yao Xie
2022	A*	`conf`	PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. ICML Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
2022	J	`jnl`	PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. CoRR Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
2021	J	`jnl`	Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data. CoRR Shixiang Zhu, Alexander Bukharin, Liyan Xie, Shihao Yang, Pinar Keskinocak, Yao Xie
2021	J	`jnl`	High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S. ACM Trans. Manag. Inf. Syst. Shixiang Zhu, Alexander Bukharin, Liyan Xie, Mauricio Santillana, Shihao Yang, Yao Xie