3 papers
cs.LG2026
Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
Jie Cheng, Ruixi Qiao, Yingwei Ma +5
A significant aspiration of offline reinforcement learning (RL) is to develop a generalist agent with high capabilities from large and heterogeneous datasets. However, prior approa…
cs.LG2025
Offline Reinforcement Learning with Discrete Diffusion Skills
RuiXi Qiao, Jie Cheng, Xingyuan Dai +2
Skills have been introduced to offline reinforcement learning (RL) as temporal abstractions to tackle complex, long-horizon tasks, promoting consistent behavior and enabling meanin…
cs.LG2024
RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences
Jie Cheng, Gang Xiong, Xingyuan Dai +3
Preference-based Reinforcement Learning (PbRL) circumvents the need for reward engineering by harnessing human preferences as the reward signal. However, current PbRL methods exces…