Kianté Brantley

Research:

I am an Assistant Professor of Computer Science at Kempner Institute and School of Engineering and Applied Sciences (SEAS), Harvard University. I study imitation learning and interactive learning—or, more broadly, settings that involve a feedback loop between a machine learning agent and the input the machine learning agent sees.

Prospective Students:

I am actively recruiting new PhD students with a strong background in applied reinforcement learning, natural language processing, machine learning, and deep learning. If you are applying to Harvard, please mention my name in your research statement. For already admitted Harvard PhD students, please send me your CV and a brief description of your research interest.

Recent Publications:

Coactive Learning for Large Language Models using Implicit User Feedback

Tucker, Aaron David and Brantley, Kianté and Cahall, Adam and Joachims, Thorsten

Proceedings of the International Conference on Machine Learning (ICML), 2024

[Arxiv]

REBEL: Reinforcement Learning via Regressing Relative Rewards

Gao, Zhaolin and Chang, Jonathan D and Zhan, Wenhao and Oertell, Owen and Swamy, Gokul and Brantley, Kianté and Joachims, Thorsten and Bagnell, J Andrew and Lee, Jason D and Sun, Wen

Preprint, 2024

[Arxiv]

Dataset Reset Policy Optimization for RLHF

Chang, Jonathan D and Shan, Wenhao and Oertell, Owen and Brantley, Kianté and Misra, Dipendra and Lee, Jason D and Sun, Wen

Preprint, 2024

[Arxiv]

RL for Consistency Models: Faster Reward Guided Text-to-Image Generation

Oertell, Owen and Chang, Jonathan D and Zhang, Yiyi and Brantley, Kianté and Sun, Wen

Preprint, 2024

[Arxiv]