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cs.LG2025
TreeGRPO: Tree-Advantage GRPO for Online RL Post-Training of Diffusion Models
Zheng Ding, Weirui Ye
Reinforcement learning (RL) post-training is crucial for aligning generative models with human preferences, but its prohibitive computational cost remains a major barrier to widesp…
cs.LG2024
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
Shengjie Wang, Shaohuai Liu, Weirui Ye +2
Sample efficiency remains a crucial challenge in applying Reinforcement Learning (RL) to real-world tasks. While recent algorithms have made significant strides in improving sample…
cs.LG2022★ 2 cited
Planning for Sample Efficient Imitation Learning
Zhao-Heng Yin, Weirui Ye, Qifeng Chen +1
Imitation learning is a class of promising policy learning algorithms that is free from many practical issues with reinforcement learning, such as the reward design issue and the e…