Zibin Dong / 董子斌
Master student at TJU Deep Reinforcement Learning Lab.
I am a master student at the TJU Deep Reinforcement Learning Lab, advised by Prof. Jianye Hao and co-advised by Prof. Yan Zheng. I received my Bachelor’s degree from the Harbin Institution of Technology (Shenzhen) (HITsz) in 2023, advised by Prof. Qingbin Gao.
My research interests primarily focus on developing embodied agents for decision-making. To accomplish this goal, my current research encompasses Reinforcement Learning (RL): Offline RL, Model-based RL, RL from Human Feedback (RLHF), Diffusion Models for decision-making, and LLM agents. I aspire to leverage the transformative power of AI in shaping the world. I am highly self-motivated and possess a strong passion for AI research. I am constantly seeking opportunities for research collaborations, research interns, and PhD. You can find detailed information about me in my CV. Feel free to contact me at zibindong@outlook.com.
news
Jan 15, 2024 | Two papers accepted by ICLR 2024: “Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model”, “Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback” |
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Aug 05, 2023 | One paper accepted by CIKM 2023: “A Hierarchical Imitation Learning-based Decision Framework for Autonomous Driving” |
selected publications
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- AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion ModelIn The Twelfth International Conference on Learning Representations, ICLR , 2024
- Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human FeedbackIn The Twelfth International Conference on Learning Representations, ICLR , 2024
- A Hierarchical Imitation Learning-based Decision Framework for Autonomous DrivingIn Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM , 2023