Alexander Bukharin

According to our database, Alexander Bukharin authored at least 14 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

HelpSteer2-Preference: Complementing Ratings with Preferences.

Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong

CoRR, 2024

RNR: Teaching Large Language Models to Follow Roles and Rules.

Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li

CoRR, 2024

Robust Reinforcement Learning from Corrupted Human Feedback.

Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao

CoRR, 2024

Adaptive Preference Scaling for Reinforcement Learning with Human Feedback.

Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao

CoRR, 2024

Data Diversity Matters for Robust Instruction Tuning.

Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, Haoming Jiang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Data Diversity Matters for Robust Instruction Tuning.

Alexander Bukharin, Tuo Zhao

CoRR, 2023

Deep Reinforcement Learning from Hierarchical Weak Preference Feedback.

Alexander Bukharin, Yixiao Li, Pengcheng He, Weizhu Chen, Tuo Zhao

CoRR, 2023

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms.

Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Machine Learning Force Fields with Data Cost Aware Training.

Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

Proceedings of the International Conference on Machine Learning, 2023

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data.

Shixiang Zhu, Alexander Bukharin, Liyan Xie, Khurram Yamin, Shihao Yang, Pinar Keskinocak, Yao Xie

IEEE J. Sel. Top. Signal Process., 2022

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance.

Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao

Proceedings of the International Conference on Machine Learning, 2022

2021

High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S.

Shixiang Zhu, Alexander Bukharin, Liyan Xie, Mauricio Santillana, Shihao Yang, Yao Xie

ACM Trans. Manag. Inf. Syst., 2021

Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data.

Shixiang Zhu, Alexander Bukharin, Liyan Xie, Shihao Yang, Pinar Keskinocak, Yao Xie

CoRR, 2021